IMT Institutional Repository: No conditions. Results ordered -Date Deposited.
2022-08-12T17:08:00Z
EPrints
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2018-03-09T13:43:01Z
2018-03-09T13:43:01Z
http://eprints.imtlucca.it/id/eprint/4038
This item is in the repository with the URL: http://eprints.imtlucca.it/id/eprint/4038
2018-03-09T13:43:01Z
Enhanced capital-asset pricing model for the reconstruction of bipartite financial networks
Reconstructing patterns of interconnections from partial information is one of the most important issues in the statistical physics of complex networks. A paramount example is provided by financial networks. In fact, the spreading and amplification of financial distress in capital markets are strongly affected by the interconnections among financial institutions. Yet, while the aggregate balance sheets of institutions are publicly disclosed, information on single positions is mostly confidential and, as such, unavailable. Standard approaches to reconstruct the network of financial interconnection produce unrealistically dense topologies, leading to a biased estimation of systemic risk. Moreover, reconstruction techniques are generally designed for monopartite networks of bilateral exposures between financial institutions, thus failing in reproducing bipartite networks of security holdings (e.g., investment portfolios). Here we propose a reconstruction method based on constrained entropy maximization, tailored for bipartite financial networks. Such a procedure enhances the traditional capital-asset pricing model (CAPM) and allows us to reproduce the correct topology of the network. We test this enhanced CAPM (ECAPM) method on a dataset, collected by the European Central Bank, of detailed security holdings of European institutional sectors over a period of six years (2009–2015). Our approach outperforms the traditional CAPM and the recently proposed maximum-entropy CAPM both in reproducing the network topology and in estimating systemic risk due to fire sales spillovers. In general, ECAPM can be applied to the whole class of weighted bipartite networks described by the fitness model.
Tiziano Squartini
tiziano.squartini@imtlucca.it
Assaf Almog
Guido Caldarelli
guido.caldarelli@imtlucca.it
Iman van Lelyveld
Diego Garlaschelli
diego.garlaschelli@imtlucca.it
Giulio Cimini
giulio.cimini@imtlucca.it
2018-03-02T11:48:35Z
2018-03-02T11:48:35Z
http://eprints.imtlucca.it/id/eprint/3933
This item is in the repository with the URL: http://eprints.imtlucca.it/id/eprint/3933
2018-03-02T11:48:35Z
Management Science for Complex Networks and Smart Water Grids: a case study in Italy
As the effects of climate change unfold and become more visible, infrastruc- tures, especially those related to the distribution of water are the most exposed to the deep changes expected in the next years. Water is fundamental for peo- ple, and for infrastructures like energy, waste, and food production. Water sus- tainability is then a fundamental aspect to address by an efficient use of the resources and the maintenance of quality standards adopting a management science perspective. Therefore, water industry and infrastructure need a deep transformation, and we claim that this transformation is the result of a synergy between different fields or research. Our paper presents a managerial framework based on a complex systems used to reshape and optimize in different meanings the performance of the water infrastructure through the development of a case study in Italy. Our framework, called Acque 2.0 (Water 2.0) is based on these pillars: 1. The current and future scenarios for water management 2. Management science and water 3. Digitalization of water infrastructure 4. Increase the network resiliency and quality of service using complex networks 5. Use of predic- tive maintenance methods based on network simulations and big data 6. Involve utilities, regulators, policy makers, and citizens 7. Remarks and conclusion. The case study will be developed in the municipality of Viareggio, characterized by old infrastructures, seasonal variation of population, and water scarcity.
Nicola Lattanzi
nicola.lattanzi@imtlucca.it
Angelo Facchini
angelo.facchini@imtlucca.it
Guido Caldarelli
guido.caldarelli@imtlucca.it
Antonio Scala
Giovanni Liberatore
2018-01-16T10:04:27Z
2018-01-16T10:04:27Z
http://eprints.imtlucca.it/id/eprint/3861
This item is in the repository with the URL: http://eprints.imtlucca.it/id/eprint/3861
2018-01-16T10:04:27Z
The Network of U.S. Mutual Fund Investments: Diversification, Similarity and Fragility throughout the
Global Financial Crisis
Network theory proved recently to be useful in the quantification of many properties of financial systems. The analysis of the structure of investment portfolios is a major application since their eventual correlation and overlap impact the actual risk diversification by individual investors. We
nvestigate the bipartite network of US mutual fund portfolios and their assets. We follow its evolution during the Global Financial Crisis and analyse the interplay between diversification, as understood in classical portfolio theory, and similarity of the investments of different funds. We show that, on average, portfolios have become more diversified and less similar during the crisis. However, we also find that large overlap is far more likely than expected from models of random allocation of investments. This indicates the existence of strong correlations between fund portfolio strategies. We introduce a simplified model of propagation of financial shocks, that we exploit to show that a systemic risk component origins from the similarity of portfolios. The network is still vulnerable after crisis because of this effect, despite the increase in the diversification of portfolios. Our results indicate that diversification may even increase systemic risk when funds diversify in the same way. Diversification and similarity can play antagonistic roles and the trade-off between the two should be taken into account to properly assess systemic risk.
Danilo Delpini
Stefano Battiston
Guido Caldarelli
guido.caldarelli@imtlucca.it
Massimo Riccaboni
massimo.riccaboni@imtlucca.it
2018-01-16T09:53:09Z
2018-01-16T09:53:09Z
http://eprints.imtlucca.it/id/eprint/3859
This item is in the repository with the URL: http://eprints.imtlucca.it/id/eprint/3859
2018-01-16T09:53:09Z
A Complex Network Approach for the Estimation of the Energy Demand of Electric Mobility
We study how renewable energy impacts regional infrastructures considering the full deployment of electric mobility at that scale. We use the Sardinia Island in Italy as a paradigmatic case study of a semi-closed system both by energy and mobility point of view. Human mobility patterns are estimated by means of census data listing the mobility dynamics of about 700,000 vehicles, the energy demand is estimated by modeling the charging behavior of electric vehicle owners. Here we show that current renewable energy production of Sardinia is able to sustain the commuter mobility even in the theoretical case of a full switch from internal combustion vehicles to electric ones. Centrality measures from network theory on the reconstructed network of commuter trips allows to identify the most important areas (hubs) involved in regional mobility. The analysis of the expected energy flows reveals long-range effects on infrastructures outside metropolitan areas and points out that the most relevant unbalances are caused by spatial segregation between production and consumption areas. Finally, results suggest the adoption of planning actions supporting the installation of renewable energy plants in areas mostly involved by the commuting mobility, avoiding spatial segregation between consumption and generation areas.
Mario Mureddu
Angelo Facchini
angelo.facchini@imtlucca.it
Antonio Scala
Guido Caldarelli
guido.caldarelli@imtlucca.it
Alfonso Damiano
2017-08-07T10:21:11Z
2017-08-07T10:31:16Z
http://eprints.imtlucca.it/id/eprint/3762
This item is in the repository with the URL: http://eprints.imtlucca.it/id/eprint/3762
2017-08-07T10:21:11Z
Inferring monopartite projections of bipartite networks: an entropy-based approach
Bipartite networks are currently regarded as providing a major insight into the organization of many real-world systems, unveiling the mechanisms driving the interactions occurring between distinct groups of nodes. One of the most important issues encountered when modeling bipartite networks is devising a way to obtain a (monopartite) projection on the layer of interest, which preserves as much as possible the information encoded into the original bipartite structure. In the present paper we propose an algorithm to obtain statistically-validated projections of bipartite networks, according to which any two nodes sharing a statistically-significant number of neighbors are linked. Since assessing the statistical significance of nodes similarity requires a proper statistical benchmark, here we consider a set of four null models, defined within the exponential random graph framework. Our algorithm outputs a matrix of link-specific p -values, from which a validated projection is straightforwardly obtainable, upon running a multiple hypothesis testing procedure. Finally, we test our method on an economic network (i.e. the countries-products World Trade Web representation) and a social network (i.e. MovieLens, collecting the users’ ratings of a list of movies). In both cases non-trivial communities are detected: while projecting the World Trade Web on the countries layer reveals modules of similarly-industrialized nations, projecting it on the products layer allows communities characterized by an increasing level of complexity to be detected; in the second case, projecting MovieLens on the films layer allows clusters of movies whose affinity cannot be fully accounted for by genre similarity to be individuated.
Fabio Saracco
fabio.saracco@imtlucca.it
Mika J. Straka
mika.straka@imtlucca.it
Riccardo Di Clemente
Andrea Gabrielli
Guido Caldarelli
guido.caldarelli@imtlucca.it
Tiziano Squartini
tiziano.squartini@imtlucca.it
2017-08-04T11:32:46Z
2017-08-04T11:32:46Z
http://eprints.imtlucca.it/id/eprint/3757
This item is in the repository with the URL: http://eprints.imtlucca.it/id/eprint/3757
2017-08-04T11:32:46Z
Mapping social dynamics on Facebook: The Brexit debate
Abstract Nowadays users get informed and shape their opinion through social media. However, the disintermediated access to contents does not guarantee quality of information. Selective exposure and confirmation bias, indeed, have been shown to play a pivotal role in content consumption and information spreading. Users tend to select information adhering (and reinforcing) their worldview and to ignore dissenting information. This pattern elicits the formation of polarized groups – i.e., echo chambers – where the interaction with like-minded people might even reinforce polarization. In this work we address news consumption around Brexit in {UK} on Facebook. In particular, we perform a massive analysis on more than 1 million users interacting with Brexit related posts from the main news providers between January and July 2016. We show that consumption patterns elicit the emergence of two distinct communities of news outlets. Furthermore, to better characterize inner group dynamics, we introduce a new technique which combines automatic topic extraction and sentiment analysis. We compare how the same topics are presented on posts and the related emotional response on comments finding significant differences in both echo chambers and that polarization influences the perception of topics. Our results provide important insights about the determinants of polarization and evolution of core narratives on online debating.
Michela Del Vicario
michela.delvicario@imtlucca.it
Fabiana Zollo
fabiana.zollo@imtlucca.it
Guido Caldarelli
guido.caldarelli@imtlucca.it
Antonio Scala
Walter Quattrociocchi
walter.quattrociocchi@imtlucca.it
2017-08-04T08:43:58Z
2017-08-04T08:43:58Z
http://eprints.imtlucca.it/id/eprint/3738
This item is in the repository with the URL: http://eprints.imtlucca.it/id/eprint/3738
2017-08-04T08:43:58Z
River Networks and Optimal Channel Networks
River networks represent a perfect example of a physical
phenomenon that can be described by means of graph theory.
Water collected by rainfall flows from one point to another
one (downstream) in the river basin creates a spanning (water
flows uniformly on the terrain and therefore from every point
of the basin we have water flow) tree (water cannot flow uphill).
Rivers on Earth and even those that might have been
present on Mars all display similar statistical properties
thereby calling for a model based on basic properties.
A class of models named Optimal Channel Networks (OCN) derive
the final configuration by minimising a given cost function.
The physical inspiration for the minimization problem traces
back to the ideas of Nobel laureate Prigogine on a general
theory of irreversible processes in open dissipative systems.
Actually, theoretical results from OCN allowed to provide an
explanation to universal allometric behaviour in a variety
of different physical situations from species distribution to food webs optimisation alternative to the traditional
approach. In the specific case of river networks, the OCN
model postulates that the total gravitational energy loss in the
system is minimised. Empirical and theoretical works focus
generally on two dimensional case, while recently (inspired by
vascular systems) also the three dimensional case has been
analysed.
Here we devise some new analytical results that illustrate
the role and the properties of the structure that minimises
the cost function proposed in the ABM and we also provide
some insight about the structure of the absolute minimum by varying some of the parameters of the model. In what follows we will give a theoretical characterization of river networks and provide a simple rule to distinguish spanning trees from natural river trees. Furthermore, we extend the study of OCNs embedded on a lattice finding a lower and upper bound for the energy of an OCN in any dimension D.
Paul Balister
Jószef Balogh
Béla Bollobás
Guido Caldarelli
guido.caldarelli@imtlucca.it
Rossana Mastrandrea
rossana.mastrandrea@imtlucca.it
Rob Morris
2017-08-03T07:18:17Z
2017-08-03T07:18:17Z
http://eprints.imtlucca.it/id/eprint/3732
This item is in the repository with the URL: http://eprints.imtlucca.it/id/eprint/3732
2017-08-03T07:18:17Z
Organization and hierarchy of the human functional brain network lead to a chain-like core
The brain is a paradigmatic example of a complex system: its functionality emerges as a global property of local mesoscopic and microscopic interactions. Complex network theory allows to elicit the functional architecture of the brain in terms of links (correlations) between nodes (grey matter regions) and to extract information out of the noise. Here we present the analysis of functional magnetic resonance imaging data from forty healthy humans at rest for the investigation of the basal scaffold of the functional brain network organization. We show how brain regions tend to coordinate by forming ahighly hierarchical chain-like structure of homogeneously clustered anatomical areas. A maximum spanning tree approach revealed the centrality of the occipital cortex and the peculiar aggregation of
cerebellar regions to form a closed core. We also report the hierarchy of network segregation and the level of clusters integration as a function of the connectivity strength between brain regions.
Rossana Mastrandrea
rossana.mastrandrea@imtlucca.it
Andrea Gabrielli
Fabrizio Piras
Gianfranco Spalletta
Guido Caldarelli
guido.caldarelli@imtlucca.it
Tommaso Gili
2017-04-18T08:57:40Z
2017-04-18T08:57:40Z
http://eprints.imtlucca.it/id/eprint/3689
This item is in the repository with the URL: http://eprints.imtlucca.it/id/eprint/3689
2017-04-18T08:57:40Z
Modeling confirmation bias and polarization
Online users tend to select claims that adhere to their system of beliefs and to ignore dissenting information. Confirmation bias, indeed, plays a pivotal role in viral phenomena. Furthermore, the wide availability of content on the web fosters the aggregation of likeminded people where debates tend to enforce group polarization. Such a configuration might alter the public debate and thus the formation of the public opinion. In this paper we provide a mathematical model to study online social debates and the related polarization dynamics. We assume the basic updating rule of the Bounded Confidence Model (BCM) and we develop two variations a) the Rewire with Bounded Confidence Model (RBCM), in which discordant links are broken until convergence is reached; and b) the Unbounded Confidence Model, under which the interaction among discordant pairs of users is allowed even with a negative feedback, either with the rewiring step (RUCM) or without it (UCM). From numerical simulations we find that the new models (UCM and RUCM), unlike the BCM, are able to explain the coexistence of two stable final opinions, often observed in reality. Lastly, we present a mean field approximation of the newly introduced models.
Michela Del Vicario
michela.delvicario@imtlucca.it
Antonio Scala
Guido Caldarelli
guido.caldarelli@imtlucca.it
H. Eugene Stanley
Walter Quattrociocchi
walter.quattrociocchi@imtlucca.it
2017-04-18T08:35:43Z
2017-08-04T11:33:20Z
http://eprints.imtlucca.it/id/eprint/3686
This item is in the repository with the URL: http://eprints.imtlucca.it/id/eprint/3686
2017-04-18T08:35:43Z
Anatomy of news consumption on Facebook
The advent of social media and microblogging platforms has radically changed the way we consume information and form opinions. In this paper, we explore the anatomy of the information space on Facebook by characterizing on a global scale the news consumption patterns of 376 million users over a time span of 6 y (January 2010 to December 2015). We find that users tend to focus on a limited set of pages, producing a sharp community structure among news outlets. We also find that the preferences of users and news providers differ. By tracking how Facebook pages “like” each other and examining their geolocation, we find that news providers are more geographically confined than users. We devise a simple model of selective exposure that reproduces the observed connectivity patterns.
Ana Lucía Schmidt
Fabiana Zollo
fabiana.zollo@imtlucca.it
Michela Del Vicario
michela.delvicario@imtlucca.it
Alessandro Bessi
Antonio Scala
Guido Caldarelli
guido.caldarelli@imtlucca.it
H. Eugene Stanley
Walter Quattrociocchi
walter.quattrociocchi@imtlucca.it
2017-04-18T08:25:38Z
2017-04-18T08:25:38Z
http://eprints.imtlucca.it/id/eprint/3684
This item is in the repository with the URL: http://eprints.imtlucca.it/id/eprint/3684
2017-04-18T08:25:38Z
Mapping social dynamics on Facebook: The Brexit debate
Abstract Nowadays users get informed and shape their opinion through social media. However, the disintermediated access to contents does not guarantee quality of information. Selective exposure and confirmation bias, indeed, have been shown to play a pivotal role in content consumption and information spreading. Users tend to select information adhering (and reinforcing) their worldview and to ignore dissenting information. This pattern elicits the formation of polarized groups – i.e., echo chambers – where the interaction with like-minded people might even reinforce polarization. In this work we address news consumption around Brexit in {UK} on Facebook. In particular, we perform a massive analysis on more than 1 million users interacting with Brexit related posts from the main news providers between January and July 2016. We show that consumption patterns elicit the emergence of two distinct communities of news outlets. Furthermore, to better characterize inner group dynamics, we introduce a new technique which combines automatic topic extraction and sentiment analysis. We compare how the same topics are presented on posts and the related emotional response on comments finding significant differences in both echo chambers and that polarization influences the perception of topics. Our results provide important insights about the determinants of polarization and evolution of core narratives on online debating.
Michela Del Vicario
Fabiana Zollo
fabiana.zollo@imtlucca.it
Guido Caldarelli
guido.caldarelli@imtlucca.it
Antonio Scala
Walter Quattrociocchi
walter.quattrociocchi@imtlucca.it
2016-10-04T12:24:38Z
2016-10-04T12:24:38Z
http://eprints.imtlucca.it/id/eprint/3555
This item is in the repository with the URL: http://eprints.imtlucca.it/id/eprint/3555
2016-10-04T12:24:38Z
Coupling News Sentiment with Web Browsing Data Improves Prediction of Intra-Day Price Dynamics
The new digital revolution of big data is deeply changing our capability of understanding society and forecasting the outcome of many social and economic systems. Unfortunately, information can be very heterogeneous in the importance, relevance, and surprise it conveys, affecting severely the predictive power of semantic and statistical methods. Here we show that the aggregation of web users’ behavior can be elicited to overcome this problem in a hard to predict complex system, namely the financial market. Specifically, our in-sample analysis shows that the combined use of sentiment analysis of news and browsing activity of users of Yahoo! Finance greatly helps forecasting intra-day and daily price changes of a set of 100 highly capitalized US stocks traded in the period 2012–2013. Sentiment analysis or browsing activity when taken alone have very small or no predictive power. Conversely, when considering a news signal where in a given time interval we compute the average sentiment of the clicked news, weighted by the number of clicks, we show that for nearly 50% of the companies such signal Granger-causes hourly price returns. Our result indicates a “wisdom-of-the-crowd” effect that allows to exploit users’ activity to identify and weigh properly the relevant and surprising news, enhancing considerably the forecasting power of the news sentiment.
Wei-Xing Zhou
Gabriele Ranco
gabriele.ranco@imtlucca.it
Ilaria Bordino
Giacomo Bormetti
Guido Caldarelli
guido.caldarelli@imtlucca.it
Fabrizio Lillo
Michele Treccani
2016-10-04T11:19:22Z
2016-10-04T11:19:22Z
http://eprints.imtlucca.it/id/eprint/3554
This item is in the repository with the URL: http://eprints.imtlucca.it/id/eprint/3554
2016-10-04T11:19:22Z
Users Polarization on Facebook and Youtube
On social media algorithms for content promotion, accounting for users preferences, might limit the exposure to unsolicited contents. In this work, we study how the same contents (videos) are consumed on different platforms -- i.e. Facebook and YouTube -- over a sample of 12M of users. Our findings show that the same content lead to the formation of echo chambers, irrespective of the online social network and thus of the algorithm for content promotion. Finally, we show that the users' commenting patterns are accurate early predictors for the formation of echo-chambers.
Alessandro Bessi
Fabiana Zollo
fabiana.zollo@imtlucca.it
Michela Del Vicario
michela.delvicario@imtlucca.it
Michelangelo Puliga
michelangelo.puliga@imtlucca.it
Antonio Scala
Guido Caldarelli
guido.caldarelli@imtlucca.it
Brian Uzzi
Walter Quattrociocchi
walter.quattrociocchi@imtlucca.it
2016-10-04T10:57:25Z
2016-10-04T11:02:28Z
http://eprints.imtlucca.it/id/eprint/3552
This item is in the repository with the URL: http://eprints.imtlucca.it/id/eprint/3552
2016-10-04T10:57:25Z
The price of complexity in financial networks
Financial institutions form multilayer networks by engaging in contracts with each other and by holding exposures to common assets. As a result, the default probability of one institution depends on the default probability of all of the other institutions in the network. Here, we show how small errors on the knowledge of the network of contracts can lead to large errors in the probability of systemic defaults. From the point of view of financial regulators, our findings show that the complexity of financial networks may decrease the ability to mitigate systemic risk, and thus it may increase the social cost of financial crises.
Stefano Battiston
Guido Caldarelli
guido.caldarelli@imtlucca.it
Robert M. May
Tarik Roukny
Joseph E. Stiglitz
2016-10-04T10:38:55Z
2016-10-04T10:38:55Z
http://eprints.imtlucca.it/id/eprint/3550
This item is in the repository with the URL: http://eprints.imtlucca.it/id/eprint/3550
2016-10-04T10:38:55Z
Pathways towards instability in financial networks
There is growing consensus that processes of market integration and risk diversification may come at the price of more systemic risk. Indeed, financial institutions are interconnected in a network of contracts where distress can either be amplified or dampened. However, a mathematical understanding of instability in relation to the network topology is still lacking. In a model financial network, we show that the origin of instability resides in the presence of specific types of cyclical structures, regardless of many of the details of the distress propagation mechanism. In particular, we show the existence of trajectories in the space of graphs along which a complex network turns from stable to unstable, although at each point along the trajectory its nodes satisfy constraints that would apparently make them individually stable. In the financial context, our findings have important implications for policies aimed at increasing financial stability. We illustrate the propositions on a sample dataset for the top 50 EU listed banks between 2008 and 2013. More in general, our results shed light on previous findings on the instability of model ecosystems and are relevant for a broad class of dynamical processes on complex networks.
Marco Bardoscia
Stefano Battiston
Fabio Caccioli
Guido Caldarelli
guido.caldarelli@imtlucca.it
2016-10-04T10:25:49Z
2016-10-04T10:25:49Z
http://eprints.imtlucca.it/id/eprint/3549
This item is in the repository with the URL: http://eprints.imtlucca.it/id/eprint/3549
2016-10-04T10:25:49Z
Cascades in interdependent flow networks
In this manuscript, we investigate the abrupt breakdown behavior of coupled distribution grids under load growth. This scenario mimics the ever-increasing customer demand and the foreseen introduction of energy hubs interconnecting the different energy vectors. We extend an analytical model of cascading behavior due to line overloads to the case of interdependent networks and find evidence of first order transitions due to the long-range nature of the flows. Our results indicate that the foreseen increase in the couplings between the grids has two competing effects: on the one hand, it increases the safety region where grids can operate without withstanding systemic failures; on the other hand, it increases the possibility of a joint systems’ failure.
Antonio Scala
Pier Giorgio De Sanctis Lucentini
Guido Caldarelli
guido.caldarelli@imtlucca.it
Gregorio D’Agostino
2016-10-04T10:15:14Z
2016-10-04T10:15:14Z
http://eprints.imtlucca.it/id/eprint/3548
This item is in the repository with the URL: http://eprints.imtlucca.it/id/eprint/3548
2016-10-04T10:15:14Z
Concurrent enhancement of percolation and synchronization in adaptive networks
Co-evolutionary adaptive mechanisms are not only ubiquitous in nature, but also beneficial for the functioning of a variety of systems. We here consider an adaptive network of oscillators with a stochastic, fitness-based, rule of connectivity, and show that it self-organizes from fragmented and incoherent states to connected and synchronized ones. The synchronization and percolation are associated to abrupt transitions, and they are concurrently (and significantly) enhanced as compared to the non-adaptive case. Finally we provide evidence that only partial adaptation is sufficient to determine these enhancements. Our study, therefore, indicates that inclusion of simple adaptive mechanisms can efficiently describe some emergent features of networked systems' collective behaviors, and suggests also self-organized ways to control synchronization and percolation in natural and social systems.
Young-Ho Eom
youngho.eom@imtlucca.it
Stefano Boccaletti
Guido Caldarelli
guido.caldarelli@imtlucca.it
2016-09-22T16:17:07Z
2016-09-22T16:17:07Z
http://eprints.imtlucca.it/id/eprint/3542
This item is in the repository with the URL: http://eprints.imtlucca.it/id/eprint/3542
2016-09-22T16:17:07Z
Data Science and Complex Networks. Real Case Studies with Python
This book provides a comprehensive yet short description of the basic concepts of Complex Network theory. In contrast to other books the authors present these concepts through real case studies. The application topics span from Foodwebs, to the Internet, the World Wide Web and the Social Networks, passing through the International Trade Web and Financial time series. The final part is devoted to definition and implementation of the most important network models.
The text provides information on the structure of the data and on the quality of available datasets. Furthermore it provides a series of codes to allow immediate implementation of what is theoretically described in the book. Readers already used to the concepts introduced in this book can learn the art of coding in Python by using the online material. To this purpose the authors have set up a dedicated web site where readers can download and test the codes. The whole project is aimed as a learning tool for scientists and practitioners, enabling them to begin working instantly in the field of Complex Networks.
Guido Caldarelli
guido.caldarelli@imtlucca.it
Alessandro Chessa
alessandro.chessa@imtlucca.it
2016-06-15T07:29:33Z
2016-06-15T07:29:33Z
http://eprints.imtlucca.it/id/eprint/3501
This item is in the repository with the URL: http://eprints.imtlucca.it/id/eprint/3501
2016-06-15T07:29:33Z
Distress propagation in complex networks: the case of non-linear DebtRank
We consider a dynamical model of distress propagation on complex networks, which we apply to the study of financial contagion in networks of banks connected to each other by direct exposures. The model that we consider is an extension of the DebtRank algorithm, recently introduced in the literature. The mechanics of distress propagation is very simple: When a bank suffers a loss, distress propagates to its creditors, who in turn suffer losses, and so on. The original DebtRank assumes that losses are propagated linearly between connected banks. Here we relax this assumption and introduce a one-parameter family of non-linear propagation functions. As a case study, we apply this algorithm to a data-set of 183 European banks, and we study how the stability of the system depends on the non-linearity parameter under different stress-test scenarios. We find that the system is characterized by a transition between a regime where small shocks can be amplified and a regime where shocks do not propagate, and that the overall the stability of the system increases between 2008 and 2013.
Marco Bardoscia
Fabio Caccioli
Juan Ignacio Perotti
juanignacio.perotti@imtlucca.it
Gianna Vivaldo
gianna.vivaldo@imtlucca.it
Guido Caldarelli
guido.caldarelli@imtlucca.it
2016-06-15T07:23:45Z
2016-06-15T07:23:45Z
http://eprints.imtlucca.it/id/eprint/3499
This item is in the repository with the URL: http://eprints.imtlucca.it/id/eprint/3499
2016-06-15T07:23:45Z
Networks of plants: how to measure similarity in vegetable species
Despite the common misconception of nearly static organisms, plants do interact continuously with the environment and with each other. It is fair to assume that during their evolution they developed particular features to overcome similar problems and to exploit possibilities from environment. In this paper we introduce various quantitative measures based on recent advancements in complex network theory that allow to measure the effective similarities of various species. By using this approach on the similarity in fruit-typology ecological traits we obtain a clear plant classification in a way similar to traditional taxonomic classification. This result is not trivial, since a similar analysis done on the basis of diaspore morphological properties do not provide any clear parameter to classify plants species. Complex network theory can then be used in order to determine which feature amongst many can be used to distinguish scope and possibly evolution of plants. Future uses of this approach range from functional classification to quantitative determination of plant communities in nature.
Gianna Vivaldo
gianna.vivaldo@imtlucca.it
Elisa Masi
Camilla Pandolfi
Stefano Mancuso
Guido Caldarelli
guido.caldarelli@imtlucca.it
2016-04-07T09:17:11Z
2016-04-07T09:17:11Z
http://eprints.imtlucca.it/id/eprint/3392
This item is in the repository with the URL: http://eprints.imtlucca.it/id/eprint/3392
2016-04-07T09:17:11Z
Bootstrapping Topological Properties and Systemic Risk of Complex Networks Using the Fitness Model
In this paper we present a novel method to reconstruct global topological properties of a complex network starting from limited information. We assume to know for all the nodes a non-topological quantity that we interpret as fitness. In contrast, we assume to know the degree, i.e. the number of connections, only for a subset of the nodes in the network. We then use a fitness model, calibrated on the subset of nodes for which degrees are known, in order to generate ensembles of networks. Here, we focus on topological properties that are relevant for processes of contagion and distress propagation in networks, i.e. network density and k-core structure, and
Nicolò Musmeci
Stefano Battiston
Guido Caldarelli
guido.caldarelli@imtlucca.it
Michelangelo Puliga
michelangelo.puliga@imtlucca.it
Andrea Gabrielli
2016-04-07T09:10:32Z
2016-04-07T09:10:32Z
http://eprints.imtlucca.it/id/eprint/3390
This item is in the repository with the URL: http://eprints.imtlucca.it/id/eprint/3390
2016-04-07T09:10:32Z
Competitors' communities and taxonomy of products according to export fluxes
In this paper we use Complex Network Theory to quantitatively characterize and synthetically describe the complexity of trade between nations. In particular, we focus our attention on export fluxes. Starting from the bipartite countries-products network defined by export fluxes, we define two complementary graphs projecting the original network on countries and products respectively. We define, in both cases, a distance matrix amongst countries and products. Specifically, two countries are similar if they export similar products. This relationship can be quantified by building the Minimum Spanning Tree and the Minimum Spanning Forest from the distance matrices for products and countries. Through this simple and scalable method we are also able to carry out a community analysis. It is not gone unnoticed that in this way we can produce an effective categorization for products providing several advantages with respect to traditional classifications of COMTRADE 1. Finally, the forests of countries allows for the detection of competitors' community and for the analysis of the evolution of these communities.
Matthieu Cristelli
Andrea Tacchella
Andrea Gabrielli
Luciano Pietronero
Antonio Scala
Guido Caldarelli
guido.caldarelli@imtlucca.it
2016-03-21T08:41:12Z
2016-03-21T08:41:12Z
http://eprints.imtlucca.it/id/eprint/3240
This item is in the repository with the URL: http://eprints.imtlucca.it/id/eprint/3240
2016-03-21T08:41:12Z
Parcellation-based connectome assessment by using structural and functional connectivity
Connectome analysis of the human brain structural and functional architecture provides a unique opportunity to understand the organization of brain networks. In this work, we investigate a novel large scale parcellation-based connectome, merging together information coming from resting state fMRI (rs-fMRI) data and diffusion tensor imaging (DTI) measurements.
Ying-Chia Lin
yingchia.lin@imtlucca.it
Tommaso Gili
Sotirios A. Tsaftaris
Andrea Gabrielli
Mariangela Iorio
Gianfranco Spalletta
Guido Caldarelli
guido.caldarelli@imtlucca.it
2016-03-21T08:41:04Z
2016-03-21T08:41:04Z
http://eprints.imtlucca.it/id/eprint/3239
This item is in the repository with the URL: http://eprints.imtlucca.it/id/eprint/3239
2016-03-21T08:41:04Z
A cortical and sub-cortical parcellation clustering by intrinsic functional connectivity
Network analysis of resting-state fMRI (rsfMRI) has been widely utilized to investigate the functional architecture of the whole brain. Here we propose a robust parcellation method that first divides cortical and sub-cortical regions into sub-regions by clustering the rsfMRI data for each subject independently, and then merges those individual parcellations to obtain a global whole brain parcellation. To do so our method relies on majority voting (to merge parcellations of multiple subjects) and enforces spatial constraints within a hierarchical agglomerative clustering framework to define parcels that are spatially homogeneous.
Ying-Chia Lin
yingchia.lin@imtlucca.it
Tommaso Gili
Sotirios A. Tsaftaris
Andrea Gabrielli
Mariangela Iorio
Gianfranco Spalletta
Guido Caldarelli
guido.caldarelli@imtlucca.it
2016-03-14T13:02:02Z
2016-04-06T10:06:19Z
http://eprints.imtlucca.it/id/eprint/3223
This item is in the repository with the URL: http://eprints.imtlucca.it/id/eprint/3223
2016-03-14T13:02:02Z
A Cortical and Sub-cortical Parcellation Clustering by Intrinsic Functional Connectivity
Network analysis of resting-state fMRI (rsfMRI) has been widely utilized to investigate the functional architecture of the whole brain. Such analysis can divide the brain into several discrete elements (nodes) connected by links (edges) representing the relation between two elements. The brain cortical and subcortical areas can be segmented or parcelled into several functional and/or structural regions. The connectome analysis of human-brain structure and functional connectivity provides a unique opportunity to understand the organisation of brain networks. However, such analyses require an appropriate definition of functional or structural nodes to efficiently represent cortical regions. In order to address this issue, here we propose a robust parcellation method based on resting-state fMRI, which can be generalized from the single-subject level to the multi-group one. Considering the input data of a single subject and constructing multi-resolution graph elements. We combined voting-based measurements to divide the cortical region into sub-regions in order to obtain the whole brain parcellation. Our parcellation relies on majority vote and poses spatial constraints within a hierarchical agglomerative clustering framework to define parcels that are spatially homogeneous. We used rsfMRI data collected from 40 healthy subjects and we showed that our purposed algorithm is able to compute stable and reproducible parcellations across the group of subjects at multi-resolution level. We find that, even though previous methods ensure on average larger overlap between parcels and regions in AAL atlas, the method proposed herein reduces inter-subject variability, especially when the number of parcels increases. Our high-resolution parcels seem to be functionally more consistent and reliable and can be a useful tool for future analysis that will aim to match functional and structural architecture of the brain.
Ying-Chia Lin
yingchia.lin@imtlucca.it
Tommaso Gili
Sotirios A. Tsaftaris
sotirios.tsaftaris@imtlucca.it
Andrea Gabrielli
Mariangela Iorio
Gianfranco Spalletta
Guido Caldarelli
guido.caldarelli@imtlucca.it
2016-01-20T08:59:10Z
2016-01-20T09:37:24Z
http://eprints.imtlucca.it/id/eprint/3021
This item is in the repository with the URL: http://eprints.imtlucca.it/id/eprint/3021
2016-01-20T08:59:10Z
Viral Misinformation: The Role of Homophily and Polarization
Alessandro Bessi
Fabio Petroni
Michela Del Vicario
michela.delvicario@imtlucca.it
Fabiana Zollo
fabiana.zollo@imtlucca.it
Aris Anagnostopoulos
Antonio Scala
Guido Caldarelli
guido.caldarelli@imtlucca.it
Walter Quattrociocchi
walter.quattrociocchi@imtlucca.it
2016-01-20T08:51:59Z
2016-01-20T09:37:06Z
http://eprints.imtlucca.it/id/eprint/3020
This item is in the repository with the URL: http://eprints.imtlucca.it/id/eprint/3020
2016-01-20T08:51:59Z
The spreading of misinformation online
The wide availability of user-provided content in online social media facilitates the aggregation of people around common interests, worldviews, and narratives. However, the World Wide Web (WWW) also allows for the rapid dissemination of unsubstantiated rumors and conspiracy theories that often elicit rapid, large, but naive social responses such as the recent case of Jade Helm 15––where a simple military exercise turned out to be perceived as the beginning of a new civil war in the United States. In this work, we address the determinants governing misinformation spreading through a thorough quantitative analysis. In particular, we focus on how Facebook users consume information related to two distinct narratives: scientific and conspiracy news. We find that, although consumers of scientific and conspiracy stories present similar consumption patterns with respect to content, cascade dynamics differ. Selective exposure to content is the primary driver of content diffusion and generates the formation of homogeneous clusters, i.e., “echo chambers.” Indeed, homogeneity appears to be the primary driver for the diffusion of contents and each echo chamber has its own cascade dynamics. Finally, we introduce a data-driven percolation model mimicking rumor spreading and we show that homogeneity and polarization are the main determinants for predicting cascades’ size.
Michela Del Vicario
michela.delvicario@imtlucca.it
Alessandro Bessi
Fabiana Zollo
fabiana.zollo@imtlucca.it
Fabio Petroni
Antonio Scala
Guido Caldarelli
guido.caldarelli@imtlucca.it
H. Eugene Stanley
Walter Quattrociocchi
walter.quattrociocchi@imtlucca.it
2015-12-03T15:37:21Z
2018-03-08T17:02:20Z
http://eprints.imtlucca.it/id/eprint/2966
This item is in the repository with the URL: http://eprints.imtlucca.it/id/eprint/2966
2015-12-03T15:37:21Z
Optimal Scales in Weighted Networks
The analysis of networks characterized by links with heterogeneous intensity or weight suffers from two long-standing problems of arbitrariness. On one hand, the definitions of topological properties introduced for binary graphs can be generalized in non-unique ways to weighted networks. On the other hand, even when a definition is given, there is no natural choice of the (optimal) scale of link intensities (e.g. the money unit in economic networks). Here we show that these two seemingly independent problems can be regarded as intimately related, and propose a common solution to both. Using a formalism that we recently proposed in order to map a weighted network to an ensemble of binary graphs, we introduce an information-theoretic approach leading to the least biased generalization of binary properties to weighted networks, and at the same time fixing the optimal scale of link intensities. We illustrate our method on various social and economic networks.
Diego Garlaschelli
diego.garlaschelli@imtlucca.it
Sebastian E. Ahnert
Thomas M.A. Fink
Guido Caldarelli
guido.caldarelli@imtlucca.it
2015-12-03T14:50:46Z
2015-12-03T14:50:46Z
http://eprints.imtlucca.it/id/eprint/2963
This item is in the repository with the URL: http://eprints.imtlucca.it/id/eprint/2963
2015-12-03T14:50:46Z
Social Determinants of Content Selection in the Age of (Mis)Information
Despite the enthusiastic rhetoric about the so called collective intelligence, conspiracy theories – e.g. global warming induced by chemtrails or the link between vaccines and autism – find on the Web a natural medium for their dissemination. Users preferentially consume information according to their system of beliefs and the strife within users of opposite worldviews (e.g., scientific and conspiracist) may result in heated debates. In this work we provide a genuine example of information consumption on a set of 1.2 million of Facebook Italian users. We show by means of a thorough quantitative analysis that information supporting different worldviews – i.e. scientific and conspiracist news – are consumed in a comparable way. Moreover, we measure the effect of 4709 evidently false information (satirical version of conspiracist stories) and 4502 debunking memes (information aiming at contrasting unsubstantiated rumors) on polarized users of conspiracy claims.
Alessandro Bessi
Guido Caldarelli
guido.caldarelli@imtlucca.it
Michela Del Vicario
michela.delvicario@imtlucca.it
Antonio Scala
Walter Quattrociocchi
walter.quattrociocchi@imtlucca.it
2015-11-02T14:20:02Z
2015-11-02T14:20:02Z
http://eprints.imtlucca.it/id/eprint/2801
This item is in the repository with the URL: http://eprints.imtlucca.it/id/eprint/2801
2015-11-02T14:20:02Z
Quantifying randomness in real networks
Represented as graphs, real networks are intricate combinations of order and disorder. Fixing some of the structural properties of network models to their values observed in real networks, many other properties appear as statistical consequences of these fixed observables, plus randomness in other respects. Here we employ the dk-series, a complete set of basic characteristics of the network structure, to study the statistical dependencies between different network properties. We consider six real networks—the Internet, US airport network, human protein interactions, technosocial web of trust, English word network, and an fMRI map of the human brain—and find that many important local and global structural properties of these networks are closely reproduced by dk-random graphs whose degree distributions, degree correlations and clustering are as in the corresponding real network. We discuss important conceptual, methodological, and practical implications of this evaluation of network randomness, and release software to generate dk-random graphs.
Chiara Orsini
Marija M. Dankulov
Pol Colomer-de-Simón
Almerima Jamakovic
Priya Mahadevan
Amin Vahdat
Kevin E. Bassler
Zoltán Toroczkai
Marián Boguñá
Guido Caldarelli
guido.caldarelli@imtlucca.it
Santo Fortunato
Dmitri Krioukov
2015-11-02T14:08:08Z
2016-05-23T09:05:25Z
http://eprints.imtlucca.it/id/eprint/2800
This item is in the repository with the URL: http://eprints.imtlucca.it/id/eprint/2800
2015-11-02T14:08:08Z
Science vs Conspiracy: Collective Narratives in the Age of Misinformation
The large availability of user provided contents on online social media facilitates people aggregation around shared beliefs, interests, worldviews and narratives. In spite of the enthusiastic rhetoric about the so called collective intelligence unsubstantiated rumors and conspiracy theories—e.g., chemtrails, reptilians or the Illuminati—are pervasive in online social networks (OSN). In this work we study, on a sample of 1.2 million of individuals, how information related to very distinct narratives—i.e. main stream scientific and conspiracy news—are consumed and shape communities on Facebook. Our results show that polarized communities emerge around distinct types of contents and usual consumers of conspiracy news result to be more focused and self-contained on their specific contents. To test potential biases induced by the continued exposure to unsubstantiated rumors on users’ content selection, we conclude our analysis measuring how users respond to 4,709 troll information—i.e. parodistic and sarcastic imitation of conspiracy theories. We find that 77.92 of likes and 80.86 of comments are from users usually interacting with conspiracy stories.
Alessandro Bessi
Mauro Coletto
mauro.coletto@imtlucca.it
George Alexandru Davidescu
Antonio Scala
Guido Caldarelli
guido.caldarelli@imtlucca.it
Walter Quattrociocchi
walter.quattrociocchi@imtlucca.it
2015-11-02T14:00:36Z
2015-11-02T14:01:57Z
http://eprints.imtlucca.it/id/eprint/2799
This item is in the repository with the URL: http://eprints.imtlucca.it/id/eprint/2799
2015-11-02T14:00:36Z
DebtRank: A Microscopic Foundation for Shock Propagation
The DebtRank algorithm has been increasingly investigated as a method to estimate the impact of shocks in financial networks, as it overcomes the limitations of the traditional default-cascade approaches. Here we formulate a dynamical “microscopic” theory of instability for financial networks by iterating balance sheet identities of individual banks and by assuming a simple rule for the transfer of shocks from borrowers to lenders. By doing so, we generalise the DebtRank formulation, both providing an interpretation of the effective dynamics in terms of basic accounting principles and preventing the underestimation of losses on certain network topologies. Depending on the structure of the interbank leverage matrix the dynamics is either stable, in which case the asymptotic state can be computed analytically, or unstable, meaning that at least one bank will default. We apply this framework to a dataset of the top listed European banks in the period 2008–2013. We find that network effects can generate an amplification of exogenous shocks of a factor ranging between three (in normal periods) and six (during the crisis) when we stress the system with a 0.5 shock on external (i.e. non-interbank) assets for all banks.
Marco Bardoscia
Stefano Battiston
Fabio Caccioli
Guido Caldarelli
guido.caldarelli@imtlucca.it
2015-11-02T13:56:36Z
2015-11-02T13:56:36Z
http://eprints.imtlucca.it/id/eprint/2798
This item is in the repository with the URL: http://eprints.imtlucca.it/id/eprint/2798
2015-11-02T13:56:36Z
Twitter-Based Analysis of the Dynamics of Collective Attention to Political Parties
Large-scale data from social media have a significant potential to describe complex phenomena in the real world and to anticipate collective behaviors such as information spreading and social trends. One specific case of study is represented by the collective attention to the action of political parties. Not surprisingly, researchers and stakeholders tried to correlate parties' presence on social media with their performances in elections. Despite the many efforts, results are still inconclusive since this kind of data is often very noisy and significant signals could be covered by (largely unknown) statistical fluctuations. In this paper we consider the number of tweets (tweet volume) of a party as a proxy of collective attention to the party, identify the dynamics of the volume, and show that this quantity has some information on the election outcome. We find that the distribution of the tweet volume for each party follows a log-normal distribution with a positive autocorrelation of the volume over short terms, which indicates the volume has large fluctuations of the log-normal distribution yet with a short-term tendency. Furthermore, by measuring the ratio of two consecutive daily tweet volumes, we find that the evolution of the daily volume of a party can be described by means of a geometric Brownian motion (i.e., the logarithm of the volume moves randomly with a trend). Finally, we determine the optimal period of averaging tweet volume for reducing fluctuations and extracting short-term tendencies. We conclude that the tweet volume is a good indicator of parties' success in the elections when considered over an optimal time window. Our study identifies the statistical nature of collective attention to political issues and sheds light on how to model the dynamics of collective attention in social media.
Young-Ho Eom
youngho.eom@imtlucca.it
Michelangelo Puliga
michelangelo.puliga@imtlucca.it
Jasmina Smailović
Igor Mozetič
Guido Caldarelli
guido.caldarelli@imtlucca.it
2015-11-02T13:48:19Z
2015-11-02T13:48:19Z
http://eprints.imtlucca.it/id/eprint/2796
This item is in the repository with the URL: http://eprints.imtlucca.it/id/eprint/2796
2015-11-02T13:48:19Z
Trend of Narratives in the Age of Misinformation
Social media enabled a direct path from producer to consumer of contents changing the way users get informed, debate, and shape their worldviews. Such a disintermediation might weaken consensus on social relevant issues in favor of rumors, mistrust, or conspiracy thinking—e.g., chem-trails inducing global warming, the link between vaccines and autism, or the New World Order conspiracy. Previous studies pointed out that consumers of conspiracy-like content are likely to aggregate in homophile clusters—i.e., echo-chambers. Along this path we study, by means of a thorough quantitative analysis, how different topics are consumed inside the conspiracy echo-chamber in the Italian Facebook. Through a semi-automatic topic extraction strategy, we show that the most consumed contents semantically refer to four specific categories: environment, diet, health, and geopolitics. We find similar consumption patterns by comparing users activity (likes and comments) on posts belonging to these different semantic categories. Finally, we model users mobility across the distinct topics finding that the more a user is active, the more he is likely to span on all categories. Once inside a conspiracy narrative users tend to embrace the overall corpus.
Alessandro Bessi
Fabiana Zollo
fabiana.zollo@imtlucca.it
Michela Del Vicario
michela.delvicario@imtlucca.it
Antonio Scala
Guido Caldarelli
guido.caldarelli@imtlucca.it
Walter Quattrociocchi
walter.quattrociocchi@imtlucca.it
2015-11-02T13:44:15Z
2015-11-02T13:48:55Z
http://eprints.imtlucca.it/id/eprint/2795
This item is in the repository with the URL: http://eprints.imtlucca.it/id/eprint/2795
2015-11-02T13:44:15Z
Green Power Grids: How Energy from Renewable Sources Affects Networks and Markets
The increasing attention to environmental issues is forcing the implementation of novel energy models based on renewable sources. This is fundamentally changing the configuration of energy management and is introducing new problems that are only partly understood. In particular, renewable energies introduce fluctuations which cause an increased request for conventional energy sources to balance energy requests at short notice. In order to develop an effective usage of low-carbon sources, such fluctuations must be understood and tamed. In this paper we present a microscopic model for the description and for the forecast of short time fluctuations related to renewable sources in order to estimate their effects on the electricity market. To account for the inter-dependencies in the energy market and the physical power dispatch network, we use a statistical mechanics approach to sample stochastic perturbations in the power system and an agent based approach for the prediction of the market players’ behavior. Our model is data-driven; it builds on one-day-ahead real market transactions in order to train agents’ behaviour and allows us to deduce the market share of different energy sources. We benchmarked our approach on the Italian market, finding a good accordance with real data.
Mario Mureddu
Guido Caldarelli
guido.caldarelli@imtlucca.it
Alessandro Chessa
alessandro.chessa@imtlucca.it
Antonio Scala
Alfonso Damiano
2015-11-02T13:37:08Z
2015-11-02T13:37:08Z
http://eprints.imtlucca.it/id/eprint/2793
This item is in the repository with the URL: http://eprints.imtlucca.it/id/eprint/2793
2015-11-02T13:37:08Z
The Effects of Twitter Sentiment on Stock Price Returns
Social media are increasingly reflecting and influencing behavior of other complex systems. In this paper we investigate the relations between a well-known micro-blogging platform Twitter and financial markets. In particular, we consider, in a period of 15 months, the Twitter volume and sentiment about the 30 stock companies that form the Dow Jones Industrial Average (DJIA) index. We find a relatively low Pearson correlation and Granger causality between the corresponding time series over the entire time period. However, we find a significant dependence between the Twitter sentiment and abnormal returns during the peaks of Twitter volume. This is valid not only for the expected Twitter volume peaks (e.g., quarterly announcements), but also for peaks corresponding to less obvious events. We formalize the procedure by adapting the well-known “event study” from economics and finance to the analysis of Twitter data. The procedure allows to automatically identify events as Twitter volume peaks, to compute the prevailing sentiment (positive or negative) expressed in tweets at these peaks, and finally to apply the “event study” methodology to relate them to stock returns. We show that sentiment polarity of Twitter peaks implies the direction of cumulative abnormal returns. The amount of cumulative abnormal returns is relatively low (about 1–2), but the dependence is statistically significant for several days after the events.
Gabriele Ranco
Darko Aleksovski
Guido Caldarelli
guido.caldarelli@imtlucca.it
Miha Grčar
Igor Mozetič
2015-11-02T13:32:38Z
2015-11-02T13:32:38Z
http://eprints.imtlucca.it/id/eprint/2792
This item is in the repository with the URL: http://eprints.imtlucca.it/id/eprint/2792
2015-11-02T13:32:38Z
Hyperbolicity measures democracy in real-world networks
In this work, we analyze the hyperbolicity of real-world networks, a geometric quantity that measures if a space is negatively curved. We provide two improvements in our understanding of this quantity: first of all, in our interpretation, a hyperbolic network is “aristocratic”, since few elements “connect” the system, while a non-hyperbolic network has a more “democratic” structure with a larger number of crucial elements. The second contribution is the introduction of the average hyperbolicity of the neighbors of a given node. Through this definition, we outline an “influence area” for the vertices in the graph. We show that in real networks the influence area of the highest degree vertex is small in what we define “local” networks (i.e., social or peer-to-peer networks), and large in “global” networks (i.e., power grid, metabolic networks, or autonomous system networks).
Michele Borassi
Alessandro Chessa
alessandro.chessa@imtlucca.it
Guido Caldarelli
guido.caldarelli@imtlucca.it
2015-11-02T13:27:41Z
2015-11-02T13:27:41Z
http://eprints.imtlucca.it/id/eprint/2791
This item is in the repository with the URL: http://eprints.imtlucca.it/id/eprint/2791
2015-11-02T13:27:41Z
Emotional Dynamics in the Age of Misinformation
According to the World Economic Forum, the diffusion of unsubstantiated rumors on online social media is one of the main threats for our society. The disintermediated paradigm of content production and consumption on online social media might foster the formation of homogeneous communities (echo-chambers) around specific worldviews. Such a scenario has been shown to be a vivid environment for the diffusion of false claim. Not rarely, viral phenomena trigger naive (and funny) social responses—e.g., the recent case of Jade Helm 15 where a simple military exercise turned out to be perceived as the beginning of the civil war in the US. In this work, we address the emotional dynamics of collective debates around distinct kinds of information—i.e., science and conspiracy news—and inside and across their respective polarized communities. We find that for both kinds of content the longer the discussion the more the negativity of the sentiment. We show that comments on conspiracy posts tend to be more negative than on science posts. However, the more the engagement of users, the more they tend to negative commenting (both on science and conspiracy). Finally, zooming in at the interaction among polarized communities, we find a general negative pattern. As the number of comments increases—i.e., the discussion becomes longer—the sentiment of the post is more and more negative.
Fabiana Zollo
fabiana.zollo@imtlucca.it
Petra Kralj Novak
Michela Del Vicario
michela.delvicario@imtlucca.it
Alessandro Bessi
Igor Mozetič
Antonio Scala
Guido Caldarelli
guido.caldarelli@imtlucca.it
Walter Quattrociocchi
walter.quattrociocchi@imtlucca.it
2015-10-28T15:00:56Z
2015-10-28T15:00:56Z
http://eprints.imtlucca.it/id/eprint/2788
This item is in the repository with the URL: http://eprints.imtlucca.it/id/eprint/2788
2015-10-28T15:00:56Z
Debunking in a World of Tribes
Recently a simple military exercise on the Internet was perceived as the beginning of a new civil war in the US. Social media aggregate people around common interests eliciting a collective framing of narratives and worldviews. However, the wide availability of user-provided content and the direct path between producers and consumers of information often foster confusion about causations, encouraging mistrust, rumors, and even conspiracy thinking. In order to contrast such a trend attempts to \textit{debunk} are often undertaken. Here, we examine the effectiveness of debunking through a quantitative analysis of 54 million users over a time span of five years (Jan 2010, Dec 2014). In particular, we compare how users interact with proven (scientific) and unsubstantiated (conspiracy-like) information on Facebook in the US. Our findings confirm the existence of echo chambers where users interact primarily with either conspiracy-like or scientific pages. Both groups interact similarly with the information within their echo chamber. We examine 47,780 debunking posts and find that attempts at debunking are largely ineffective. For one, only a small fraction of usual consumers of unsubstantiated information interact with the posts. Furthermore, we show that those few are often the most committed conspiracy users and rather than internalizing debunking information, they often react to it negatively. Indeed, after interacting with debunking posts, users retain, or even increase, their engagement within the conspiracy echo chamber.
Fabiana Zollo
fabiana.zollo@imtlucca.it
Alessandro Bessi
Michela Del Vicario
michela.delvicario@imtlucca.it
Antonio Scala
Guido Caldarelli
guido.caldarelli@imtlucca.it
Louis Shekhtman
Shlomo Havlin
Walter Quattrociocchi
walter.quattrociocchi@imtlucca.it
2015-05-21T10:00:39Z
2016-04-07T09:49:34Z
http://eprints.imtlucca.it/id/eprint/2698
This item is in the repository with the URL: http://eprints.imtlucca.it/id/eprint/2698
2015-05-21T10:00:39Z
Default Cascades in Complex Networks: Topology and Systemic Risk
The recent crisis has brought to the fore a crucial question that remains still open: what would be the optimal architecture of financial systems? We investigate the stability of several benchmark topologies in a simple default cascading dynamics in bank networks. We analyze the interplay of several crucial drivers, i.e., network topology, banks' capital ratios, market illiquidity, and random vs targeted shocks. We find that, in general, topology matters only – but substantially – when the market is illiquid. No single topology is always superior to others. In particular, scale-free networks can be both more robust and more fragile than homogeneous architectures. This finding has important policy implications. We also apply our methodology to a comprehensive dataset of an interbank market from 1999 to 2011.
Tarik Roukny
Hugues Bersini
Hugues Pirotte
Guido Caldarelli
guido.caldarelli@imtlucca.it
Stefano Battiston
2015-05-21T09:00:30Z
2015-05-21T09:00:30Z
http://eprints.imtlucca.it/id/eprint/2695
This item is in the repository with the URL: http://eprints.imtlucca.it/id/eprint/2695
2015-05-21T09:00:30Z
An agent based approach for the development of EV fleet Charging Strategies in Smart Cities
In the present paper an agent based approach, addressed to simulate the behaviour of a Plug-in Electric Vehicles (PEV) fleet into a Smart City, is presented. Considering the traffic data-set available from mobility plans, a spatial and time model, representing the evolution of travel patterns, can be developed considering each vehicle as an agent. The following statistical analysis in space and time of the agent behaviours is used to plan the PEV charging infrastructure of municipalities. The proposed planning methodology has been tested on an European city in order to evaluate the effectiveness of the proposed procedure. Such charging infrastructure, defined according to the mobility needs, has been tested and used to evaluate the customer satisfaction of PEV users in term of charging demand. The proposed charging system has been implemented to estimate the average daily energy profiles for charging the smart city PEV fleet during a typical workday. This has been finally used as one day ahead energy reference profile to develop a market-oriented EV charging strategies. The performance of the proposed smart charging strategies has been finally simulated and compared.
Mario Mureddu
Alfonso Damiano
M. Musio
Guido Caldarelli
guido.caldarelli@imtlucca.it
Alessandro Chessa
alessandro.chessa@imtlucca.it
Antonio Scala
2015-05-21T08:52:50Z
2015-11-02T09:56:19Z
http://eprints.imtlucca.it/id/eprint/2694
This item is in the repository with the URL: http://eprints.imtlucca.it/id/eprint/2694
2015-05-21T08:52:50Z
Integrating the electric grid and the commuter
network through a “Vehicle to Grid” concept: a Complex Networks Theory approach
The new opportunities in the energy production,
storage and distribution, raise new systemic challenges in the
coordination and integration of each element in the infras-
tructural networks, considering also the unavoidable environ-
mental constraints. In this ’multi-network’ scenario an exciting
prospective is to develop the so-called vehicle-to-grid concept to
introduce a positive coupling between the electric grid and the
commuter network. The present research will use concepts and
tools borrowed from the scientific field of Complex Networks, to
understand the infrastructures’ interplay in the perspective of
modeling, simulating and possibly controlling the systemic risk.
Alessandro Chessa
alessandro.chessa@imtlucca.it
Guido Caldarelli
guido.caldarelli@imtlucca.it
Alfonso Damiano
Antonio Scala
2015-05-19T11:15:50Z
2015-05-19T11:15:50Z
http://eprints.imtlucca.it/id/eprint/2687
This item is in the repository with the URL: http://eprints.imtlucca.it/id/eprint/2687
2015-05-19T11:15:50Z
DebtRank: A microscopic foundation for shock propagation
The DebtRank algorithm has been increasingly investigated as a method to estimate the impact of shocks in financial networks, as it overcomes the limitations of the traditional default-cascade approaches. Here we formulate a dynamical "microscopic" theory of instability for financial networks by iterating balance sheet identities of individual banks and by assuming a simple rule for the transfer of shocks from borrowers to lenders. By doing so, we generalise the DebtRank formulation, both providing an interpretation of the effective dynamics in terms of basic accounting principles and preventing the underestimation of losses on certain network topologies. Depending on the structure of leverages the dynamics is either stable, in which case the asymptotic state can be computed analytically, or unstable, meaning that at least a bank will default. We apply this results to a network of roughly 200 among the largest European banks in the period 2008 - 2013. We show that network effects generate an amplification of exogenous shocks of a factor ranging between three (in normal periods) and six (during the crisis), when we stress the system with a 0.5% shock on external (i.e. non-interbank) assets for all banks.
Marco Bardoscia
Stefano Battiston
Fabio Caccioli
Guido Caldarelli
guido.caldarelli@imtlucca.it
2015-05-19T11:12:43Z
2015-05-19T11:12:43Z
http://eprints.imtlucca.it/id/eprint/2686
This item is in the repository with the URL: http://eprints.imtlucca.it/id/eprint/2686
2015-05-19T11:12:43Z
Green power grids: how energy from renewable sources affects network and markets
The increasing attention to environmental issues is forcing the implementation of novel energy models based on renewable sources, fundamentally changing the configuration of energy management and introducing new criticalities that are only partly understood. In particular, renewable energies introduce fluctuations causing an increased request of conventional energy sources oriented to balance energy requests on short notices. In order to develop an effective usage of low-carbon sources, such fluctuations must be understood and tamed. In this paper we present a microscopic model for the description and the forecast of short time fluctuations related to renewable sources and to their effects on the electricity market. To account for the inter-dependencies among the energy market and the physical power dispatch network, we use a statistical mechanics approach to sample stochastic perturbations on the power system and an agent based approach for the prediction of the market players behavior. Our model is a data-driven; it builds on one day ahead real market transactions to train agents behaviour and allows to infer the market share of different energy sources. We benchmark our approach on the Italian market finding a good accordance with real data.
Mario Mureddu
Guido Caldarelli
guido.caldarelli@imtlucca.it
Alessandro Chessa
alessandro.chessa@imtlucca.it
Antonio Scala
Alfonso Damiano
2015-05-19T10:14:45Z
2015-05-19T10:14:45Z
http://eprints.imtlucca.it/id/eprint/2684
This item is in the repository with the URL: http://eprints.imtlucca.it/id/eprint/2684
2015-05-19T10:14:45Z
Leveraging the network: a stress-test framework based on DebtRank
We develop a novel stress-test framework to monitor systemic risk in financial systems. The modular structure of the framework allows to accommodate for a variety of shock scenarios, methods to estimate interbank exposures and mechanisms of distress propagation. The main features are as follows. First, the framework allows to estimate and disentangle not only first-round effects (i.e. shock on external assets) and second-round effects (i.e. distress induced in the interbank network), but also third-round effects induced by possible fire sales. Second, it allows to monitor at the same time the impact of shocks on individual or groups of financial institutions as well as their vulnerability to shocks on counterparties or certain asset classes. Third, it includes estimates for loss distributions, thus combining network effects with familiar risk measures such as VaR and CVaR. Fourth, in order to perform robustness analyses and cope with incomplete data, the framework features a module for the generation of sets of networks of interbank exposures that are coherent with the total lending and borrowing of each bank. As an illustration, we carry out a stress-test exercise on a dataset of listed European banks over the years 2008-2013. We find that second-round and third-round effects dominate first-round effects, therefore suggesting that most current stress-test frameworks might lead to a severe underestimation of systemic risk.
Stefano Battiston
Marco D'Errico
Stefano Gurciullo
Guido Caldarelli
guido.caldarelli@imtlucca.it
2015-05-19T10:05:19Z
2015-05-19T10:05:19Z
http://eprints.imtlucca.it/id/eprint/2683
This item is in the repository with the URL: http://eprints.imtlucca.it/id/eprint/2683
2015-05-19T10:05:19Z
Trend of Narratives in the Age of Misinformation
Social media enabled a direct path from producer to consumer of contents changing the way users get informed, debate, and shape their worldviews. Such a {\em disintermediation} weakened consensus on social relevant issues in favor of rumors, mistrust, and fomented conspiracy thinking -- e.g., chem-trails inducing global warming, the link between vaccines and autism, or the New World Order conspiracy.
In this work, we study through a thorough quantitative analysis how different conspiracy topics are consumed in the Italian Facebook. By means of a semi-automatic topic extraction strategy, we show that the most discussed contents semantically refer to four specific categories: {\em environment}, {\em diet}, {\em health}, and {\em geopolitics}. We find similar patterns by comparing users activity (likes and comments) on posts belonging to different semantic categories. However, if we focus on the lifetime -- i.e., the distance in time between the first and the last comment for each user -- we notice a remarkable difference within narratives -- e.g., users polarized on geopolitics are more persistent in commenting, whereas the less persistent are those focused on diet related topics. Finally, we model users mobility across various topics finding that the more a user is active, the more he is likely to join all topics. Once inside a conspiracy narrative users tend to embrace the overall corpus.
Alessandro Bessi
Fabiana Zollo
fabiana.zollo@imtlucca.it
Michela Del Vicario
michela.delvicario@imtlucca.it
Antonio Scala
Guido Caldarelli
guido.caldarelli@imtlucca.it
Walter Quattrociocchi
walter.quattrociocchi@imtlucca.it
2015-05-19T09:56:38Z
2016-04-06T09:52:55Z
http://eprints.imtlucca.it/id/eprint/2682
This item is in the repository with the URL: http://eprints.imtlucca.it/id/eprint/2682
2015-05-19T09:56:38Z
Twitter-based analysis of the dynamics of collective attention to political parties
Large-scale data from social media have a significant potential to describe complex phenomena in real world and to anticipate collective behaviors such as information spreading and social trends. One specific case of study is represented by the collective attention to the action of political parties. Not surprisingly, researchers and stakeholders tried to correlate parties' presence on social media with their performances in elections. Despite the many efforts, results are still inconclusive since this kind of data is often very noisy and significant signals could be covered by (largely unknown) statistical fluctuations.
In this paper we consider the number of tweets (tweet volume) of a party as a proxy of collective attention to the party, we identify the dynamics of the volume, and show that this quantity has some information on the elections outcome. We find that the distribution of the tweet volume for each party follows a log-normal distribution with a positive autocorrelation over short terms. Furthermore, by measuring the ratio of two consecutive daily tweet volumes, we find that the evolution of the daily volume of a party can be described by means of a geometric Brownian motion. Finally, we determine the optimal period of averaging tweet volume for reducing fluctuations and extracting short-term tendencies. We conclude that the tweet volume is a good indicator of parties' success in the elections when considered over an optimal time window. Our study identifies the statistical nature of collective attention to political issues and sheds light on how to model the dynamics of collective attention in social media.
Young-Ho Eom
youngho.eom@imtlucca.it
Michelangelo Puliga
michelangelo.puliga@imtlucca.it
Jasmina Smailović
Igor Mozetič
Guido Caldarelli
guido.caldarelli@imtlucca.it
2015-03-09T09:41:23Z
2018-03-08T16:57:03Z
http://eprints.imtlucca.it/id/eprint/2629
This item is in the repository with the URL: http://eprints.imtlucca.it/id/eprint/2629
2015-03-09T09:41:23Z
Reconstructing topological properties of complex networks using the fitness model
A major problem in the study of complex socioeconomic systems is represented by privacy issues—that can put severe limitations on the amount of accessible information, forcing to build models on the basis of incomplete knowledge. In this paper we investigate a novel method to reconstruct global topological properties of a complex network starting from limited information. This method uses the knowledge of an intrinsic property of the nodes (indicated as fitness), and the number of connections of only a limited subset of nodes, in order to generate an ensemble of exponential random graphs that are representative of the real systems and that can be used to estimate its topological properties. Here we focus in particular on reconstructing the most basic properties that are commonly used to describe a network: density of links, assortativity, clustering. We test the method on both benchmark synthetic networks and real economic and financial systems, finding a remarkable robustness with respect to the number of nodes used for calibration. The method thus represents a valuable tool for gaining insights on privacy-protected systems.
Giulio Cimini
giulio.cimini@imtlucca.it
Tiziano Squartini
tiziano.squartini@imtlucca.it
Nicolò Musmeci
Michelangelo Puliga
michelangelo.puliga@imtlucca.it
Andrea Gabrielli
Diego Garlaschelli
diego.garlaschelli@imtlucca.it
Stefano Battiston
Guido Caldarelli
guido.caldarelli@imtlucca.it
2015-02-02T10:25:24Z
2015-02-02T10:25:24Z
http://eprints.imtlucca.it/id/eprint/2552
This item is in the repository with the URL: http://eprints.imtlucca.it/id/eprint/2552
2015-02-02T10:25:24Z
Structural patterns of the occupy movement on Facebook
In this work we study a peculiar example of social organization on Facebook: the Occupy Movement -- i.e., an international protest movement against social and economic inequality organized online at a city level. We consider 179 US Facebook public pages during the time period between September 2011 and February 2013. The dataset includes 618K active users and 753K posts that received about 5.2M likes and 1.1M comments. By labeling user according to their interaction patterns on pages -- e.g., a user is considered to be polarized if she has at least the 95% of her likes on a specific page -- we find that activities are not locally coordinated by geographically close pages, but are driven by pages linked to major US cities that act as hubs within the various groups. Such a pattern is verified even by extracting the backbone structure -- i.e., filtering statistically relevant weight heterogeneities -- for both the pages-reshares and the pages-common users networks.
Michela Del Vicario
michela.delvicario@imtlucca.it
Qian Zhang
Alessandro Bessi
Fabiana Zollo
fabiana.zollo@imtlucca.it
Antonio Scala
Guido Caldarelli
guido.caldarelli@imtlucca.it
Walter Quattrociocchi
walter.quattrociocchi@imtlucca.it
2014-12-10T14:41:25Z
2014-12-10T14:41:25Z
http://eprints.imtlucca.it/id/eprint/2407
This item is in the repository with the URL: http://eprints.imtlucca.it/id/eprint/2407
2014-12-10T14:41:25Z
Schroedinger-like PageRank equation and localization in the WWW
The WorldWide Web is one of the most important communication systems we use in our everyday life. Despite its central role, the growth and the development of the WWW is not controlled by any central authority. This situation has created a huge ensemble of connections whose complexity can be fruitfully described and quantified by network theory. One important application that allows to sort out the information present in these connections is given by the PageRank alghorithm. Computation of this quantity is usually made iteratively with a large use of computational time. In this paper we show that the PageRank can be expressed in terms of a wave function obeying a Schroedinger-like equation. In particular the topological disorder given by the unbalance of outgoing and ingoing links between pages, induces wave function and potential structuring. This allows to directly localize the pages with the largest score. Through this new representation we can now compute the PageRank without iterative techniques. For most of the cases of interest our method is faster than the original one. Our results also clarify the role of topology in the diffusion of information within complex networks. The whole approach opens the possibility to novel techniques inspired by quantum physics for the analysis of the WWW properties.
Nicola Perra
Vinko Zlatic
Alessandro Chessa
alessandro.chessa@imtlucca.it
Claudio Conti
Debora Donato
Guido Caldarelli
guido.caldarelli@imtlucca.it
2014-12-01T10:28:46Z
2014-12-01T10:28:46Z
http://eprints.imtlucca.it/id/eprint/2377
This item is in the repository with the URL: http://eprints.imtlucca.it/id/eprint/2377
2014-12-01T10:28:46Z
Complex networks for data-driven medicine: the case of Class III dentoskeletal disharmony
In the last decade, the availability of innovative algorithms derived from complexity theory has inspired the development of highly detailed models in various fields, including physics, biology, ecology, economy, and medicine. Due to the availability of novel and ever more sophisticated diagnostic procedures, all biomedical disciplines face the problem of using the increasing amount of information concerning each patient to improve diagnosis and prevention. In particular, in the discipline of orthodontics the current diagnostic approach based on clinical and radiographic data is problematic due to the complexity of craniofacial features and to the numerous interacting co-dependent skeletal and dentoalveolar components. In this study, we demonstrate the capability of computational methods such as network analysis and module detection to extract organizing principles in 70 patients with excessive mandibular skeletal protrusion with underbite, a condition known in orthodontics as Class III malocclusion. Our results could possibly constitute a template framework for organising the increasing amount of medical data available for patients' diagnosis.
Antonio Scala
Pietro Auconi
Marco Scazzocchio
Guido Caldarelli
guido.caldarelli@imtlucca.it
James A. McNamara
Lorenzo Franchi
2014-11-17T11:46:15Z
2014-11-17T11:46:15Z
http://eprints.imtlucca.it/id/eprint/2371
This item is in the repository with the URL: http://eprints.imtlucca.it/id/eprint/2371
2014-11-17T11:46:15Z
Viral misinformation: the role of homophily and polarization
The spreading of unsubstantiated rumors on online social networks (OSN) either unintentionally or intentionally (e.g., for political reasons or even trolling) can have serious consequences such as in the recent case of rumors about Ebola causing disruption to health-care workers. Here we show that indicators aimed at quantifying information consumption patterns might provide important insights about the virality of false claims. In particular, we address the driving forces behind the popularity of contents by analyzing a sample of 1.2M Facebook Italian users consuming different (and opposite) types of information (science and conspiracy news). We show that users' engagement across different contents correlates with the number of friends having similar consumption patterns (homophily), indicating the area in the social network where certain types of contents are more likely to spread. Then, we test diffusion patterns on an external sample of 4,709 intentional satirical false claims showing that neither the presence of hubs (structural properties) nor the most active users (influencers) are prevalent in viral phenomena. Instead, we found out that in an environment where misinformation is pervasive, users' aggregation around shared beliefs may make the usual exposure to conspiracy stories (polarization) a determinant for the virality of false information.
Aris Anagnostopoulos
Alessandro Bessi
Guido Caldarelli
guido.caldarelli@imtlucca.it
Michela Del Vicario
michela.delvicario@imtlucca.it
Fabio Petroni
Antonio Scala
Fabiana Zollo
fabiana.zollo@imtlucca.it
Walter Quattrociocchi
walter.quattrociocchi@imtlucca.it
2014-11-10T09:17:33Z
2014-11-10T09:17:33Z
http://eprints.imtlucca.it/id/eprint/2351
This item is in the repository with the URL: http://eprints.imtlucca.it/id/eprint/2351
2014-11-10T09:17:33Z
Credit Default Swaps networks and systemic risk
Credit Default Swaps (CDS) spreads should reflect default risk of the underlying corporate debt. Actually, it has been recognized that CDS spread time series did not anticipate but only followed the increasing risk of default before the financial crisis. In principle, the network of correlations among CDS spread time series could at least display some form of structural change to be used as an early warning of systemic risk. Here we study a set of 176 CDS time series of financial institutions from 2002 to 2011. Networks are constructed in various ways, some of which display structural change at the onset of the credit crisis of 2008, but never before. By taking these networks as a proxy of interdependencies among financial institutions, we run stress-test based on Group DebtRank. Systemic risk before 2008 increases only when incorporating a macroeconomic indicator reflecting the potential losses of financial assets associated with house prices in the US. This approach indicates a promising way to detect systemic instabilities.
Michelangelo Puliga
michelangelo.puliga@imtlucca.it
Guido Caldarelli
guido.caldarelli@imtlucca.it
Stefano Battiston
2014-09-02T11:09:25Z
2016-05-23T09:05:54Z
http://eprints.imtlucca.it/id/eprint/2277
This item is in the repository with the URL: http://eprints.imtlucca.it/id/eprint/2277
2014-09-02T11:09:25Z
Science vs Conspiracy: collective narratives in the age of (mis)information
The large availability of user provided contents on online social media facilitates people aggregation around common interests, worldviews and narratives. However, in spite of the enthusiastic rhetoric about the so called {\em wisdom of crowds}, unsubstantiated rumors -- as alternative explanation to main stream versions of complex phenomena -- find on the Web a natural medium for their dissemination. In this work we study, on a sample of 1.2 million of individuals, how information related to very distinct narratives -- i.e. main stream scientific and alternative news -- are consumed on Facebook. Through a thorough quantitative analysis, we show that distinct communities with similar information consumption patterns emerge around distinctive narratives. Moreover, consumers of alternative news (mainly conspiracy theories) result to be more focused on their contents, while scientific news consumers are more prone to comment on alternative news. We conclude our analysis testing the response of this social system to 4709 troll information -- i.e. parodistic imitation of alternative and conspiracy theories. We find that, despite the false and satirical vein of news, usual consumers of conspiracy news are the most prone to interact with them.
Alessandro Bessi
Mauro Coletto
mauro.coletto@imtlucca.it
George Alexandru Davidescu
Antonio Scala
Guido Caldarelli
guido.caldarelli@imtlucca.it
Walter Quattrociocchi
walter.quattrociocchi@imtlucca.it
2014-09-01T12:17:22Z
2014-09-01T13:08:11Z
http://eprints.imtlucca.it/id/eprint/2271
This item is in the repository with the URL: http://eprints.imtlucca.it/id/eprint/2271
2014-09-01T12:17:22Z
The rise of China in the international trade network: a community core detection approach
Theory of complex networks proved successful in the description of a variety of complex systems ranging from biology to computer science and to economics and finance. Here we use network models to describe the evolution of a particular economic system, namely the International Trade Network (ITN). Previous studies often assume that globalization and regionalization in international trade are contradictory to each other. We re-examine the relationship between globalization and regionalization by viewing the international trade system as an interdependent complex network. We use the modularity optimization method to detect communities and community cores in the ITN during the years 1995–2011. We find rich dynamics over time both inter- and intra-communities. In particular, the Asia-Oceania community disappeared and reemerged over time along with a switch in leadership from Japan to China. We provide a multilevel description of the evolution of the network where the global dynamics (i.e., communities disappear or reemerge) and the regional dynamics (i.e., community core changes between community members) are related. Moreover, simulation results show that the global dynamics can be generated by a simple dynamic-edge-weight mechanism.
Zhen Zhu
zhen.zhu@imtlucca.it
Federica Cerina
Alessandro Chessa
alessandro.chessa@imtlucca.it
Guido Caldarelli
guido.caldarelli@imtlucca.it
Massimo Riccaboni
massimo.riccaboni@imtlucca.it
2014-06-26T12:39:17Z
2014-06-26T12:39:17Z
http://eprints.imtlucca.it/id/eprint/2211
This item is in the repository with the URL: http://eprints.imtlucca.it/id/eprint/2211
2014-06-26T12:39:17Z
An economic and financial exploratory
This paper describes the vision of a European Exploratory for economics and finance using an interdisciplinary consortium of economists, natural scientists, computer scientists and engineers, who will combine their expertise to address the enormous challenges of the 21st century. This Academic Public facility is intended for economic modelling, investigating all aspects of risk and stability, improving financial technology, and evaluating proposed regulatory and taxation changes. The European Exploratory for economics and finance will be constituted as a network of infrastructure, observatories, data repositories, services and facilities and will foster the creation of a new cross-disciplinary research community of social scientists, complexity scientists and computing (ICT) scientists to collaborate in investigating major issues in economics and finance. It is also considered a cradle for training and collaboration with the private sector to spur spin-offs and job creations in Europe in the finance and economic sectors. The Exploratory will allow Social Scientists and Regulators as well as Policy Makers and the private sector to conduct realistic investigations with real economic, financial and social data. The Exploratory will (i) continuously monitor and evaluate the status of the economies of countries in their various components, (ii) use, extend and develop a large variety of methods including data mining, process mining, computational and artificial intelligence and every other computer and complex science techniques coupled with economic theory and econometric, and (iii) provide the framework and infrastructure to perform what-if analysis, scenario evaluations and computational, laboratory, field and web experiments to inform decision makers and help develop innovative policy, market and regulation designs.
Silvano Cincotti
Didler Sornette
Philip Treleaven
Stefano Battiston
Guido Caldarelli
guido.caldarelli@imtlucca.it
Cars H. Hommes
Alan Kirman
2014-06-16T12:27:41Z
2014-09-02T09:53:17Z
http://eprints.imtlucca.it/id/eprint/2205
This item is in the repository with the URL: http://eprints.imtlucca.it/id/eprint/2205
2014-06-16T12:27:41Z
Power grids, smart grids and complex networks
We present some possible Complex Networks approaches to study and understand Power Grids and to improve them into Smart Grids . We first sketch the general properties of the Electric System with an attention to the effects of Distributed Generation. We then analyse the effects of renewable power sources on Voltage Controllability. Afterwords, we study the impact of electric line overloads on the nature of Blackouts. Finally, we discuss the possibility of implementing Self Healing capabilities into Power Grids through the use of Routing Protocols.
Antonio Scala
Guido Caldarelli
guido.caldarelli@imtlucca.it
Alessandro Chessa
alessandro.chessa@imtlucca.it
Alfonso Damiano
Mario Mureddu
Sakshi Pahwa
Caterina Scoglio
Walter Quattrociocchi
2014-06-16T12:17:10Z
2016-04-07T09:39:52Z
http://eprints.imtlucca.it/id/eprint/2204
This item is in the repository with the URL: http://eprints.imtlucca.it/id/eprint/2204
2014-06-16T12:17:10Z
Measuring the intangibles: a metrics for the economic complexity of countries and products
We investigate a recent methodology we have proposed to extract valuable information on the competitiveness of countries and complexity of products from trade data. Standard economic theories predict a high level of specialization of countries in specific industrial sectors. However, a direct analysis of the official databases of exported products by all countries shows that the actual situation is very different. Countries commonly considered as developed ones are extremely diversified, exporting a large variety of products from very simple to very complex. At the same time countries generally considered as less developed export only the products also exported by the majority of countries. This situation calls for the introduction of a non-monetary and non-income-based measure for country economy complexity which uncovers the hidden potential for development and growth. The statistical approach we present here consists of coupled non-linear maps relating the competitiveness/fitness of countries to the complexity of their products. The fixed point of this transformation defines a metrics for the fitness of countries and the complexity of products. We argue that the key point to properly extract the economic information is the non-linearity of the map which is necessary to bound the complexity of products by the fitness of the less competitive countries exporting them. We present a detailed comparison of the results of this approach directly with those of the Method of Reflections by Hidalgo and Hausmann, showing the better performance of our method and a more solid economic, scientific and consistent foundation.
Matthieu Cristelli
Andrea Gabrielli
Andrea Tacchella
Guido Caldarelli
guido.caldarelli@imtlucca.it
Luciano Pietronero
2014-06-16T12:06:17Z
2014-06-16T12:06:17Z
http://eprints.imtlucca.it/id/eprint/2202
This item is in the repository with the URL: http://eprints.imtlucca.it/id/eprint/2202
2014-06-16T12:06:17Z
Systemic risk in financial networks
Financial inter-linkages play an important role in the emergence of financial instabilities and the formulation of systemic risk can greatly benefit from a network approach. In this paper, we focus on the role of linkages along the two dimensions of contagion and liquidity, and we discuss some insights that have recently emerged from network models. With respect to the issue of the determination of the optimal architecture of the financial system, models suggest that regulators have to look at the interplay of network topology, capital requirements, and market liquidity. With respect to the issue of the determination of systemically important financial institutions the findings indicate that both from the point of view of contagion and from the point of view of liquidity provision, there is more to systemic importance than just size. In particular for contagion, the position of institutions in the network matters and their impact can be computed through stress tests even when there are no defaults in the system.topology, capital requirements, and market liquidity. With respect to the issue of the determination of systemically important financial institutions the findings indicate that both from the point of view of contagion and from the point of view of liquidity provision, there is more to systemic importance than just size. In particular for contagion, the position of institutions in the network matters and their impact can be computed through stress tests even when there are no defaults in the system.
Stefano Battiston
Guido Caldarelli
guido.caldarelli@imtlucca.it
2014-06-16T11:23:49Z
2018-03-08T17:01:43Z
http://eprints.imtlucca.it/id/eprint/2201
This item is in the repository with the URL: http://eprints.imtlucca.it/id/eprint/2201
2014-06-16T11:23:49Z
Low-Temperature behaviour of social and economic networks
Real-world social and economic networks typically display a number of particular topological properties, such as a giant connected component, a broad degree distribution, the small-world property and the presence of communities of densely interconnected nodes. Several models, including ensembles of networks, also known in social science as Exponential Random Graphs, have been proposed with the aim of reproducing each of these properties in isolation. Here, we define a generalized ensemble of graphs by introducing the concept of graph temperature, controlling the degree of topological optimization of a network. We consider the temperature-dependent version of both existing and novel models and show that all the aforementioned topological properties can be simultaneously understood as the natural outcomes of an optimized, low-temperature topology. We also show that seemingly different graph models, as well as techniques used to extract information from real networks are all found to be particular low-temperature cases of the same generalized formalism. One such technique allows us to extend our approach to real weighted networks. Our results suggest that a low graph temperature might be a ubiquitous property of real socio-economic networks, placing conditions on the diffusion of information across these systems.
Diego Garlaschelli
diego.garlaschelli@imtlucca.it
Sebastian E. Ahnert
Thomas M.A. Fink
Guido Caldarelli
guido.caldarelli@imtlucca.it
2014-06-16T11:16:52Z
2014-07-07T10:28:55Z
http://eprints.imtlucca.it/id/eprint/2200
This item is in the repository with the URL: http://eprints.imtlucca.it/id/eprint/2200
2014-06-16T11:16:52Z
Bootstrapping topological properties and systemic risk of complex networks using the fitness model
In this paper we present a novel method to reconstruct global topological properties of a complex network starting from limited information. We assume to know for all the nodes a non-topological quantity that we interpret as fitness. In contrast, we assume to know the degree, i.e. the number of connections, only for a subset of the nodes in the network. We then use a fitness model, calibrated on the subset of nodes for which degrees are known, in order to generate ensembles of networks. Here, we focus on topological properties that are relevant for processes of contagion and distress propagation in networks, i.e. network density and k-core structure, and we study how well these properties can be estimated as a function of the size of the subset of nodes utilized for the calibration. Finally, we also study how well the resilience to distress propagation in the network can be estimated using our method. We perform a first test on ensembles of synthetic networks generated with the Exponential Random Graph model, which allows to apply common tools from statistical mechanics. We then perform a second test on empirical networks taken from economic and financial contexts. In both cases, we find that a subset as small as 10 % of nodes can be enough to estimate the properties of the network along with its resilience with an error of 5 %.
Nicolò Musmeci
Stefano Battiston
Guido Caldarelli
guido.caldarelli@imtlucca.it
Michelangelo Puliga
michelangelo.puliga@imtlucca.it
Andrea Gabrielli
2014-06-03T12:50:20Z
2014-06-03T12:50:20Z
http://eprints.imtlucca.it/id/eprint/2198
This item is in the repository with the URL: http://eprints.imtlucca.it/id/eprint/2198
2014-06-03T12:50:20Z
Opinion dynamics on interacting networks: media competition and social influence
The inner dynamics of the multiple actors of the informations systems – i.e, T.V., newspapers, blogs, social network platforms, – play a fundamental role on the evolution of the public opinion. Coherently with the recent history of the information system (from few main stream media to the massive diffusion of socio-technical system), in this work we investigate how main stream media signed interaction might shape the opinion space. In particular we focus on how different size (in the number of media) and interaction patterns of the information system may affect collective debates and thus the opinions' distribution. We introduce a sophisticated computational model of opinion dynamics which accounts for the coexistence of media and gossip as separated mechanisms and for their feedback loops. The model accounts also for the effect of the media communication patterns by considering both the simple case where each medium mimics the behavior of the most successful one (to maximize the audience) and the case where there is polarization and thus competition among media memes. We show that plurality and competition within information sources lead to stable configurations where several and distant cultures coexist.
Walter Quattrociocchi
walter.quattrociocchi@imtlucca.it
Guido Caldarelli
guido.caldarelli@imtlucca.it
Antonio Scala
2014-05-13T09:07:10Z
2014-07-07T10:27:41Z
http://eprints.imtlucca.it/id/eprint/2196
This item is in the repository with the URL: http://eprints.imtlucca.it/id/eprint/2196
2014-05-13T09:07:10Z
A multi-level geographical study of Italian political elections from Twitter Data
In this paper we present an analysis of the behavior of Italian Twitter users during national political elections. We monitor the volumes of the tweets related to the leaders of the various political parties and we compare them to the elections results. Furthermore, we study the topics that are associated with the co-occurrence of two politicians in the same tweet. We cannot conclude, from a simple statistical analysis of tweet volume and their time evolution, that it is possible to precisely predict the election outcome (or at least not in our case of study that was characterized by a “too-close-to-call” scenario). On the other hand, we found that the volume of tweets and their change in time provide a very good proxy of the final results. We present this analysis both at a national level and at smaller levels, ranging from the regions composing the country to macro-areas (North, Center, South).
Guido Caldarelli
guido.caldarelli@imtlucca.it
Alessandro Chessa
alessandro.chessa@imtlucca.it
Fabio Pammolli
f.pammolli@imtlucca.it
Gabriele Pompa
gabriele.pompa@imtlucca.it
Michelangelo Puliga
michelangelo.puliga@imtlucca.it
Massimo Riccaboni
massimo.riccaboni@imtlucca.it
Gianni Riotta
2014-04-29T08:36:57Z
2014-04-29T08:36:57Z
http://eprints.imtlucca.it/id/eprint/2192
This item is in the repository with the URL: http://eprints.imtlucca.it/id/eprint/2192
2014-04-29T08:36:57Z
The rise of China in the international trade network: a community core detection approach
Theory of complex networks proved successful in the description of a variety of static networks ranging from biology to computer and social sciences and to economics and
finance. Here we use network models to describe the evolution of a particular economic system, namely the International Trade Network (ITN). Previous studies often assume that globalization and regionalization in international trade are contradictory to each other. We re-examine the relationship between globalization and regionalization by viewing the international trade system as an interdependent complex network. We use the modularity optimization method to detect communities and community cores in the ITN during the years 1995-2011. We find rich dynamics over time both inter- and intra-communities. Most importantly, we have a multilevel description of the
evolution where the global dynamics (i.e., communities disappear or reemerge) tend to be correlated with the regional dynamics (i.e., community core changes between
community members). In particular, the Asia-Oceania community disappeared and reemerged over time along with a switch in leadership from Japan to China. Moreover,
simulation results show that the global dynamics can be generated by a preferential attachment mechanism both inter- and intra- communities.
Zhen Zhu
zhen.zhu@imtlucca.it
Federica Cerina
Alessandro Chessa
alessandro.chessa@imtlucca.it
Guido Caldarelli
guido.caldarelli@imtlucca.it
Massimo Riccaboni
massimo.riccaboni@imtlucca.it
2014-01-24T14:01:24Z
2014-12-11T13:27:37Z
http://eprints.imtlucca.it/id/eprint/2125
This item is in the repository with the URL: http://eprints.imtlucca.it/id/eprint/2125
2014-01-24T14:01:24Z
Self-healing networks: redundancy and structure
We introduce the concept of self-healing in the field of complex networks modelling; in particular, self-healing capabilities are implemented through distributed communication protocols that exploit redundant links to recover the connectivity of the system. We then analyze the effect of the level of redundancy on the resilience to multiple failures; in particular, we measure the fraction of nodes still served for increasing levels of network damages. Finally, we study the effects of redundancy under different connectivity patterns—from planar grids, to small-world, up to scale-free networks—on healing performances. Small-world topologies show that introducing some long-range connections in planar grids greatly enhances the resilience to multiple failures with performances comparable to the case of the most resilient (and least realistic) scale-free structures. Obvious applications of self-healing are in the important field of infrastructural networks like gas, power, water, oil distribution systems.
Walter Quattrociocchi
walter.quattrociocchi@imtlucca.it
Guido Caldarelli
guido.caldarelli@imtlucca.it
Antonio Scala
2014-01-24T13:57:52Z
2014-01-24T13:57:52Z
http://eprints.imtlucca.it/id/eprint/2124
This item is in the repository with the URL: http://eprints.imtlucca.it/id/eprint/2124
2014-01-24T13:57:52Z
Influence of media on collective debates
The information system (T.V., newspapers, blogs, social network platforms) and its inner dynamics play a fundamental role on the evolution of collective debates and thus on the public opinion. In this work we address such a process focusing on how the current inner strategies of the information system (competition, customer satisfaction) once combined with the gossip may affect the opinions dynamics. A reinforcement effect is particularly evident in the social network platforms where several and incompatible cultures coexist (e.g, pro or against the existence of chemical trails and reptilians, the new world order conspiracy and so forth). We introduce a computational model of opinion dynamics which accounts for the coexistence of media and gossip as separated but interdependent mechanisms influencing the opinions evolution. Individuals may change their opinions under the contemporary pressure of the information supplied by the media and the opinions of their social contacts. We stress the effect of the media communication patterns by considering both the simple case where each medium mimics the behavior of the most successful one (in order to maximize the audience) and the case where there is polarization and thus competition among media reported information (in order to preserve and satisfy their segmented audience). Finally, we first model the information cycle as in the case of traditional main stream media (i.e, when every medium knows about the format of all the others) and then, to account for the effect of the Internet, on more complex connectivity patterns (as in the case of the web based information). We show that multiple and polarized information sources lead to stable configurations where several and distant opinions coexist.
Walter Quattrociocchi
walter.quattrociocchi@imtlucca.it
Guido Caldarelli
guido.caldarelli@imtlucca.it
Antonio Scala
2014-01-20T10:03:55Z
2014-01-20T10:03:55Z
http://eprints.imtlucca.it/id/eprint/2096
This item is in the repository with the URL: http://eprints.imtlucca.it/id/eprint/2096
2014-01-20T10:03:55Z
Financial Networks
The financial system performs vital functions for the world economy. Very often one of more aspect of this system can be described by means of a complex graph. In this chapter under the generic name of financial networks we indicate several different systems all related to the world of finance
Stefano Battiston
Guido Caldarelli
guido.caldarelli@imtlucca.it
2013-11-12T14:42:43Z
2013-11-20T09:15:24Z
http://eprints.imtlucca.it/id/eprint/1903
This item is in the repository with the URL: http://eprints.imtlucca.it/id/eprint/1903
2013-11-12T14:42:43Z
Distributed Generation and Resilience in Power Grids
We study the effects of the allocation of distributed generation on the resilience of power grids. We find that an unconstrained allocation and growth of the distributed generation can drive a power grid beyond its design parameters. In order to overcome such a problem, we propose a topological algorithm derived from the field of Complex Networks to allocate distributed generation sources in an existing power grid.
Antonio Scala
Mario Mureddu
Alessandro Chessa
alessandro.chessa@imtlucca.it
Guido Caldarelli
guido.caldarelli@imtlucca.it
Alfonso Damiano
2013-11-08T10:18:45Z
2013-11-08T10:18:45Z
http://eprints.imtlucca.it/id/eprint/1895
This item is in the repository with the URL: http://eprints.imtlucca.it/id/eprint/1895
2013-11-08T10:18:45Z
Integrating the electric grid and the commuter network through a 'Veichle to Grid' concept: a Complex Networks Theory approach
Alfonso Damiano
Guido Caldarelli
guido.caldarelli@imtlucca.it
Alessandro Chessa
alessandro.chessa@imtlucca.it
Antonio Scala
2013-04-29T10:06:00Z
2016-04-07T09:55:54Z
http://eprints.imtlucca.it/id/eprint/1554
This item is in the repository with the URL: http://eprints.imtlucca.it/id/eprint/1554
2013-04-29T10:06:00Z
Economic complexity: Conceptual grounding of a new metrics for global competitiveness
The availability of data corresponding to the products exported by all countries provides an excellent dataset to test economic ideas and extract new information about the process of economic development. The matrix of countries and exported products shows a marked triangular structure instead of the block-diagonal structure expected from Ricardian arguments of specialization. This observation points to the fact that diversification is instead the dominant effect in the globalized market. We discuss how to define a suitable non-monetary metrics for the value of diversification and the effective complexity of products. We discuss in detail the previous proposed approaches to assess this challenge and their limitations. We introduce a new approach to the definition of these metrics which seems to overcome the previous problems and we test it in a series of model systems.
Andrea Tacchella
Matthieu Cristelli
Guido Caldarelli
guido.caldarelli@imtlucca.it
Andrea Gabrielli
Luciano Pietronero
2013-04-15T13:48:49Z
2016-04-07T09:38:58Z
http://eprints.imtlucca.it/id/eprint/1543
This item is in the repository with the URL: http://eprints.imtlucca.it/id/eprint/1543
2013-04-15T13:48:49Z
Evolution of controllability in interbank networks
The Statistical Physics of Complex Networks has recently provided new theoretical tools for policy makers. Here we extend the notion of network controllability to detect the financial institutions, i.e. the drivers, that are most crucial to the functioning of an interbank market. The system we investigate is a paradigmatic case study for complex networks since it undergoes dramatic structural changes over time and links among nodes can be observed at several time scales. We find a scale-free decay of the fraction of drivers with increasing time resolution, implying that policies have to be adjusted to the time scales in order to be effective. Moreover, drivers are often not the most highly connected “hub” institutions, nor the largest lenders, contrary to the results of other studies. Our findings contribute quantitative indicators which can support regulators in developing more effective supervision and intervention policies.
Danilo Delpini
Stefano Battiston
Massimo Riccaboni
massimo.riccaboni@imtlucca.it
Giampaolo Gabbi
Fabio Pammolli
f.pammolli@imtlucca.it
Guido Caldarelli
guido.caldarelli@imtlucca.it
2013-03-05T09:14:39Z
2016-04-07T09:51:13Z
http://eprints.imtlucca.it/id/eprint/1504
This item is in the repository with the URL: http://eprints.imtlucca.it/id/eprint/1504
2013-03-05T09:14:39Z
Complex derivatives
The intrinsic complexity of the financial derivatives market has emerged as both an incentive to engage in it, and a key source of its inherent instability. Regulators now faced with the challenge of taming this beast may find inspiration in the budding science of complex systems.
Stefano Battiston
Guido Caldarelli
guido.caldarelli@imtlucca.it
Co-Pierre Georg
Robert May
Joseph Stiglitz
2013-03-05T09:11:29Z
2016-04-07T09:54:12Z
http://eprints.imtlucca.it/id/eprint/1503
This item is in the repository with the URL: http://eprints.imtlucca.it/id/eprint/1503
2013-03-05T09:11:29Z
Reconstructing a credit network
The science of complex networks can be usefully applied in finance, although there is limited data available with which to develop our understanding. All is not lost, however: ideas from statistical physics make it possible to reconstruct details of a financial network from partial sets of information.
Guido Caldarelli
guido.caldarelli@imtlucca.it
Alessandro Chessa
alessandro.chessa@imtlucca.it
Fabio Pammolli
f.pammolli@imtlucca.it
Andrea Gabrielli
Michelangelo Puliga
michelangelo.puliga@imtlucca.it
2013-03-04T08:37:55Z
2016-04-07T09:57:58Z
http://eprints.imtlucca.it/id/eprint/1495
This item is in the repository with the URL: http://eprints.imtlucca.it/id/eprint/1495
2013-03-04T08:37:55Z
Weighted Networks as Randomly Reinforced Urn Processes
We analyze weighted networks as randomly reinforced urn processes, in which the edge-total weights are determined by a reinforcement mechanism. We develop a new statistical test and a new procedure, based on it, to study the evolution of networks over time, detecting the “dominance”
of some edges with respect to the others and then assessing if a given instance of the network is taken at its steady state or not. Distance from the steady state can be considered as a measure of the relevance of the observed properties of the network. Our results are quite general, in the sense that they are not based on a particular probability distribution or functional form of the
random weights. Moreover, the proposed tool can be applied also to dense networks, which have received little attention by network community so far since they are often problematic. We apply our procedure in the context of the International Trade Network, determining a core of “dominant
edges”.
Guido Caldarelli
guido.caldarelli@imtlucca.it
Alessandro Chessa
alessandro.chessa@imtlucca.it
Irene Crimaldi
irene.crimaldi@imtlucca.it
Fabio Pammolli
f.pammolli@imtlucca.it
2013-01-08T11:21:19Z
2014-07-07T10:28:37Z
http://eprints.imtlucca.it/id/eprint/1459
This item is in the repository with the URL: http://eprints.imtlucca.it/id/eprint/1459
2013-01-08T11:21:19Z
DebtRank a centrality measure for financial systems and beyond
Use of network theory made possible to measure quantitatively many features of social and technological systems. In this spirit, inspired by traditional measures of centrality we introduce DebtRank a novel measure of systemic impact. We that we intend the risk of default of a large portion of the financial system, depends on the network of financial exposures among institutions. As an application, we analyse a new and unique dataset on the USD 1.2 trillion FED emergency loans program to global financial institutions during 2008--2010. We find that a group of 22 institutions, which received most of the funds, form a strongly connected graph where each of the nodes becomes systemically important at the peak of the crisis. Moreover, a systemic default could have been triggered even by small dispersed shocks. Other application to different systems are also presented.
Guido Caldarelli
guido.caldarelli@imtlucca.it
Stefano Battiston
Michelangelo Puliga
michelangelo.puliga@imtlucca.it
Rahul Kaushik
Paolo Tasca
2012-10-22T07:27:04Z
2016-04-07T09:28:16Z
http://eprints.imtlucca.it/id/eprint/1422
This item is in the repository with the URL: http://eprints.imtlucca.it/id/eprint/1422
2012-10-22T07:27:04Z
A Network Analysis of Countries’ Export Flows: Firm Grounds for the Building Blocks of the Economy
In this paper we analyze the bipartite network of countries and products from UN data on country production. We define the country-country and product-product projected networks and introduce a novel method of filtering information based on elements’ similarity. As a result we find that country clustering reveals unexpected socio-geographic links among the most competing countries. On the same footings the products clustering can be efficiently used for a bottom-up classification of produced goods. Furthermore we mathematically reformulate the “reflections method” introduced by Hidalgo and Hausmann as a fixpoint problem; such formulation highlights some conceptual weaknesses of the approach. To overcome such an issue, we introduce an alternative methodology (based on biased Markov chains) that allows to rank countries in a conceptually consistent way. Our analysis uncovers a strong non-linear interaction between the diversification of a country and the ubiquity of its products, thus suggesting the possible need of moving towards more efficient and direct non-linear fixpoint algorithms to rank countries and products in the global market.</p>
Guido Caldarelli
guido.caldarelli@imtlucca.it
Matthieu Cristelli
Andrea Gabrielli
Luciano Pietronero
Antonio Scala
Andrea Tacchella
2012-10-16T12:55:08Z
2016-04-07T09:23:37Z
http://eprints.imtlucca.it/id/eprint/1403
This item is in the repository with the URL: http://eprints.imtlucca.it/id/eprint/1403
2012-10-16T12:55:08Z
A New Metrics for Countries' Fitness and Products' Complexity
Classical economic theories prescribe specialization of countries industrial production. Inspection of the country databases of exported products shows that this is not the case: successful countries are extremely diversified, in analogy with biosystems evolving in a competitive dynamical environment. The challenge is assessing quantitatively the non-monetary competitive advantage of diversification which represents the hidden potential for development and growth. Here we develop a new statistical approach based on coupled non-linear maps, whose fixed point defines a new metrics for the country Fitness and product Complexity. We show that a non-linear iteration is necessary to bound the complexity of products by the fitness of the less competitive countries exporting them. We show that, given the paradigm of economic complexity, the correct and simplest approach to measure the competitiveness of countries is the one presented in this work. Furthermore our metrics appears to be economically well-grounded.
Andrea Tacchella
Matthieu Cristelli
Guido Caldarelli
guido.caldarelli@imtlucca.it
Andrea Gabrielli
Luciano Pietronero
2012-09-24T08:26:07Z
2012-09-24T08:26:07Z
http://eprints.imtlucca.it/id/eprint/1369
This item is in the repository with the URL: http://eprints.imtlucca.it/id/eprint/1369
2012-09-24T08:26:07Z
Using Networks To Understand Medical Data: The Case of Class III Malocclusions
<p>A system of elements that interact or regulate each other can be represented by a mathematical object called a network. While network analysis has been successfully applied to high-throughput biological systems, less has been done regarding their application in more applied fields of medicine; here we show an application based on standard medical diagnostic data. We apply network analysis to Class III malocclusion, one of the most difficult to understand and treat orofacial anomaly. We hypothesize that different interactions of the skeletal components can contribute to pathological disequilibrium; in order to test this hypothesis, we apply network analysis to 532 Class III young female patients. The topology of the Class III malocclusion obtained by network analysis shows a strong co-occurrence of abnormal skeletal features. The pattern of these occurrences influences the vertical and horizontal balance of disharmony in skeletal form and position. Patients with more unbalanced orthodontic phenotypes show preponderance of the pathological skeletal nodes and minor relevance of adaptive dentoalveolar equilibrating nodes. Furthermore, by applying Power Graphs analysis we identify some functional modules among orthodontic nodes. These modules correspond to groups of tightly inter-related features and presumably constitute the key regulators of plasticity and the sites of unbalance of the growing dentofacial Class III system. The data of the present study show that, in their most basic abstraction level, the orofacial characteristics can be represented as graphs using nodes to represent orthodontic characteristics, and edges to represent their various types of interactions. The applications of this mathematical model could improve the interpretation of the quantitative, patient-specific information, and help to better targeting therapy. Last but not least, the methodology we have applied in analyzing orthodontic features can be applied easily to other fields of the medical science.</p>
Antonio Scala
Pietro Auconi
Marco Scazzocchio
Guido Caldarelli
guido.caldarelli@imtlucca.it
James A. McNamara
Lorenzo Franchi
2012-09-19T09:58:53Z
2016-04-07T09:01:21Z
http://eprints.imtlucca.it/id/eprint/1367
This item is in the repository with the URL: http://eprints.imtlucca.it/id/eprint/1367
2012-09-19T09:58:53Z
The Longevity of Rankings
Guido Caldarelli
guido.caldarelli@imtlucca.it
2012-09-19T09:32:42Z
2012-09-19T09:32:42Z
http://eprints.imtlucca.it/id/eprint/1366
This item is in the repository with the URL: http://eprints.imtlucca.it/id/eprint/1366
2012-09-19T09:32:42Z
Progress in the physics of complex networks
Guido Caldarelli
guido.caldarelli@imtlucca.it
Giorgio Kaniadakis
Anotnio M. Scarfone
2012-09-19T09:16:35Z
2012-09-19T09:16:35Z
http://eprints.imtlucca.it/id/eprint/1365
This item is in the repository with the URL: http://eprints.imtlucca.it/id/eprint/1365
2012-09-19T09:16:35Z
Competitors’ communities and taxonomy of products according to export fluxes
In this paper we use Complex Network Theory to quantitatively characterize and synthetically describe the complexity of trade between nations. In particular, we focus our attention on export fluxes. Starting from the bipartite countries-products network defined by export fluxes, we define two complementary graphs projecting the original network on countries and products respectively. We define, in both cases, a distance matrix amongst countries and products. Specifically, two countries are similar if they export similar products. This relationship can be quantified by building the Minimum Spanning Tree and the Minimum Spanning Forest from the distance matrices for products and countries. Through this simple and scalable method we are also able to carry out a community analysis. It is not gone unnoticed that in this way we can produce an effective categorization for products providing several advantages with respect to traditional classifications of COMTRADE 1. Finally, the forests of countries allows for the detection of competitors’ community and for the analysis of the evolution of these communities.
Matthieu Cristelli
Andrea Tacchella
Andrea Gabrielli
Luciano Pietronero
Antonio Scala
Guido Caldarelli
guido.caldarelli@imtlucca.it
2012-08-07T07:49:34Z
2016-04-07T08:28:50Z
http://eprints.imtlucca.it/id/eprint/1331
This item is in the repository with the URL: http://eprints.imtlucca.it/id/eprint/1331
2012-08-07T07:49:34Z
DebtRank: Too Central to Fail? Financial Networks, the FED and Systemic Risk
Systemic risk, here meant as the risk of default of a large portion of the financial system, depends on the network of financial exposures among institutions. However, there is no widely accepted methodology to determine the systemically important nodes in a network. To fill this gap, we introduce, DebtRank, a novel measure of systemic impact inspired by feedback-centrality. As an application, we analyse a new and unique dataset on the USD 1.2 trillion FED emergency loans program to global financial institutions during 2008–2010. We find that a group of 22 institutions, which received most of the funds, form a strongly connected graph where each of the nodes becomes systemically important at the peak of the crisis. Moreover, a systemic default could have been triggered even by small dispersed shocks. The results suggest that the debate on too-big-to-fail institutions should include the even more serious issue of too-central-to-fail.
Stefano Battiston
Michelangelo Puliga
michelangelo.puliga@imtlucca.it
Rahul Kaushik
Paolo Tasca
Guido Caldarelli
guido.caldarelli@imtlucca.it
2012-07-30T11:14:52Z
2016-04-07T09:29:17Z
http://eprints.imtlucca.it/id/eprint/1328
This item is in the repository with the URL: http://eprints.imtlucca.it/id/eprint/1328
2012-07-30T11:14:52Z
Web Search Queries Can Predict Stock Market Volumes
We live in a computerized and networked society where many of our actions leave a digital trace and affect other people’s actions. This has lead to the emergence of a new data-driven research field: mathematical methods of computer science, statistical physics and sociometry provide insights on a wide range of disciplines ranging from social science to human mobility. A recent important discovery is that search engine traffic (i.e., the number of requests submitted by users to search engines on the www) can be used to track and, in some cases, to anticipate the dynamics of social phenomena. Successful examples include unemployment levels, car and home sales, and epidemics spreading. Few recent works applied this approach to stock prices and market sentiment. However, it remains unclear if trends in financial markets can be anticipated by the collective wisdom of on-line users on the web. Here we show that daily trading volumes of stocks traded in NASDAQ-100 are correlated with daily volumes of queries related to the same stocks. In particular, query volumes anticipate in many cases peaks of trading by one day or more. Our analysis is carried out on a unique dataset of queries, submitted to an important web search engine, which enable us to investigate also the user behavior. We show that the query volume dynamics emerges from the collective but seemingly uncoordinated activity of many users. These findings contribute to the debate on the identification of early warnings of financial systemic risk, based on the activity of users of the www.
Ilaria Bordino
Stefano Battiston
Guido Caldarelli
guido.caldarelli@imtlucca.it
Matthieu Cristelli
Antti Ukkonen
Ingmar Weber
2012-03-26T07:46:36Z
2016-04-07T09:48:48Z
http://eprints.imtlucca.it/id/eprint/1239
This item is in the repository with the URL: http://eprints.imtlucca.it/id/eprint/1239
2012-03-26T07:46:36Z
Robustness and assortativity for diffusion-like processes in scale-free networks
By analysing the diffusive dynamics of epidemics and of distress in complex networks, we study the effect of the assortativity on the robustness of the networks. We first determine by spectral analysis the thresholds above which epidemics/failures can spread; we then calculate the slowest diffusional times. Our results shows that disassortative networks exhibit a higher epidemiological threshold and are therefore easier to immunize, while in assortative networks there is a longer time for intervention before epidemic/failure spreads. Moreover, we study by computer simulations the sandpile cascade model, a diffusive model of distress propagation (financial contagion). We show that, while assortative networks are more prone to the propagation of epidemic/failures, degree-targeted immunization policies increases their resilience to systemic risk.
Gregorio D'Agostino
Antonio Scala
Vinko Zlatic
Guido Caldarelli
guido.caldarelli@imtlucca.it
2012-02-27T13:30:59Z
2018-03-08T17:03:15Z
http://eprints.imtlucca.it/id/eprint/1196
This item is in the repository with the URL: http://eprints.imtlucca.it/id/eprint/1196
2012-02-27T13:30:59Z
Networks with arbitrary edge multiplicities
One of the main characteristics of real-world networks is their large clustering. Clustering is one aspect of a more general but much less studied structural organization of networks, i.e. edge multiplicity, defined as the number of triangles in which edges, rather than vertices, participate. Here we show that the multiplicity distribution of real networks is in many cases scale free, and in general very broad. Thus, besides the fact that in real networks the number of edges attached to vertices often has a scale-free distribution, we find that the number of triangles attached to edges can have a scale-free distribution as well. We show that current models, even when they generate clustered networks, systematically fail to reproduce the observed multiplicity distributions. We therefore propose a generalized model that can reproduce networks with arbitrary distributions of vertex degrees and edge multiplicities, and study many of its properties analytically.
Vinko Zlatic
Diego Garlaschelli
diego.garlaschelli@imtlucca.it
Guido Caldarelli
guido.caldarelli@imtlucca.it
2012-02-27T13:18:13Z
2012-02-27T13:18:13Z
http://eprints.imtlucca.it/id/eprint/1195
This item is in the repository with the URL: http://eprints.imtlucca.it/id/eprint/1195
2012-02-27T13:18:13Z
A network approach to orthodontic diagnosis
Background – Network analysis, a recent advancement in complexity science, enables understanding of the properties of complex biological processes characterized by the interaction, adaptive regulation, and coordination of a large number of participating components.
Objective – We applied network analysis to orthodontics to detect and visualize the most interconnected clinical, radiographic, and functional data pertaining to the orofacial system.
Materials and Methods – The sample consisted of 104 individuals from 7 to 13 years of age in the mixed dentition phase without previous orthodontic intervention. The subjects were divided according to skeletal class; their clinical, radiographic, and functional features were represented as vertices (nodes) and links (edges) connecting them.
Results – Class II subjects exhibited few highly connected orthodontic features (hubs), while Class III patients showed a more compact network structure characterized by strong co-occurrence of normal and abnormal clinical, functional, and radiological features. Restricting our analysis to the highest correlations, we identified critical peculiarities of Class II and Class III malocclusions.
Conclusions – The topology of the dentofacial system obtained by network analysis could allow orthodontists to visually evaluate and anticipate the co-occurrence of auxological anomalies during individual craniofacial growth and possibly localize reactive sites for a therapeutic approach to malocclusion.
Pietro Auconi
Guido Caldarelli
guido.caldarelli@imtlucca.it
Antonio Scala
Gaetano Ierardo
Antonella Polimeni
2012-02-27T11:58:34Z
2012-02-27T11:58:34Z
http://eprints.imtlucca.it/id/eprint/1194
This item is in the repository with the URL: http://eprints.imtlucca.it/id/eprint/1194
2012-02-27T11:58:34Z
The fractal properties of internet
In this paper we show that the Internet web, from a user’s perspective, manifests robust scaling properties of the type P(n)∝n−r where n is the size of the basin connected to a given point, P represents the density of probability of finding a basin of size n connected and τ = 1.9±0.1 is a characteristic universal exponent. The connection between users and providers are studied and modeled as branches of a world spanning tree. This scale-free structure is the result of the spontaneous growth of the web, but is not necessarily the optimal one for efficient transport. We introduce an appropriate figure of merit and suggest that a planning of few big links, acting as information highways, may noticeably increase the efficiency of the net without affecting its robustness.
Riccardo Marchetti
Guido Caldarelli
guido.caldarelli@imtlucca.it
Luciano Pietronero
2012-02-27T11:35:45Z
2014-06-26T11:17:43Z
http://eprints.imtlucca.it/id/eprint/1193
This item is in the repository with the URL: http://eprints.imtlucca.it/id/eprint/1193
2012-02-27T11:35:45Z
A numerical study on the evolution of portfolio rules
In this paper we test computationally the performance of CAPM in an evolutionary setting. In particular we study the stability of distribution of wealth in a financial market where some traders invest as prescribed by CAPM and others behave according to different portfolio rules. Our study is motivated by recent analytical results that show that, whenever a logarithmic utility maximiser enters the market, CAPM traders vanish in the long run. Our analysis provides further insights and extends these results. We simulate a sequence of trades in a financial market and: first, we address the issue of how long is the long run in different parametric settings; second, we study the effect of heterogeneous savings behaviour on asymptotic wealth shares. We find that CAPM is particularly “unfit” for highly risky environments.
Guido Caldarelli
guido.caldarelli@imtlucca.it
Marina Piccioni
Emanuela Sciubba
2012-02-27T11:18:53Z
2012-02-27T12:02:28Z
http://eprints.imtlucca.it/id/eprint/1192
This item is in the repository with the URL: http://eprints.imtlucca.it/id/eprint/1192
2012-02-27T11:18:53Z
Introduction to complex networks
We present here an introduction to the ideas and models that physicist developed in order to describe the graph or network structure in a variety of different systems. Firstly we give a very basic list of definition that can be of some help in approaching this field. After that we present a brief review of the state of art for the models. © 2003 American Institute of Physics
Guido Caldarelli
guido.caldarelli@imtlucca.it
2012-02-27T10:57:19Z
2012-02-27T10:57:19Z
http://eprints.imtlucca.it/id/eprint/1191
This item is in the repository with the URL: http://eprints.imtlucca.it/id/eprint/1191
2012-02-27T10:57:19Z
The mathematics of networks: the structure of social and biological systems
Network organization is just about universal in the real world
Guido Caldarelli
guido.caldarelli@imtlucca.it
2012-02-27T10:32:54Z
2012-02-27T10:32:54Z
http://eprints.imtlucca.it/id/eprint/1190
This item is in the repository with the URL: http://eprints.imtlucca.it/id/eprint/1190
2012-02-27T10:32:54Z
Networks in cell biology
The science of complex biological networks is transforming research in areas ranging from evolutionary biology to medicine. This is the first book on the subject, providing a comprehensive introduction to complex network science and its biological applications. With contributions from key leaders in both network theory and modern cell biology, this book discusses the network science that is increasingly foundational for systems biology and the quantitative understanding of living systems. It surveys studies in the quantitative structure and dynamics of genetic regulatory networks, molecular networks underlying cellular metabolism, and other fundamental biological processes. The book balances empirical studies and theory to give a unified overview of this interdisciplinary science. It is a key introductory text for graduate students and researchers in physics, biology and biochemistry, and presents ideas and techniques from fields outside the reader's own area of specialization.
Mark Buchanan
Guido Caldarelli
guido.caldarelli@imtlucca.it
Paolo De Los Rios
Francesco Rao
Michele Vendruscolo
2012-02-27T09:59:42Z
2012-10-31T10:31:13Z
http://eprints.imtlucca.it/id/eprint/1189
This item is in the repository with the URL: http://eprints.imtlucca.it/id/eprint/1189
2012-02-27T09:59:42Z
Networks: a very short introduction
From ecosystems to Facebook, from the Internet to the global financial market, some of the most important and familiar natural systems and social phenomena are based on a networked structure. It is impossible to understand the spread of an epidemic, a computer virus, large-scale blackouts, or massive extinctions without taking into account the network structure that underlies all these phenomena.
In this Very Short Introduction, Guido Caldarelli and Michele Catanzaro discuss the nature and variety of networks, using everyday examples from society, technology, nature, and history to explain and understand the science of network theory. They show the ubiquitous role of networks; how networks self-organize; why the rich get richer; and how networks can spontaneously collapse. They conclude by highlighting how the findings of complex network theory have very wide and important applications in genetics, ecology, communications, economics, and sociology.
Guido Caldarelli
guido.caldarelli@imtlucca.it
Michele Catanzaro
2012-02-27T09:34:29Z
2012-02-27T09:34:29Z
http://eprints.imtlucca.it/id/eprint/1188
This item is in the repository with the URL: http://eprints.imtlucca.it/id/eprint/1188
2012-02-27T09:34:29Z
Fractal and topological properties of directed fractures
We use the Born model for the energy of elastic networks to simulate ‘‘directed’’ fracture growth. We define directed fractures as crack patterns showing a preferential evolution direction imposed by the type of stress and boundary conditions applied. This type of fracture allows a more realistic description of some kinds of experimental cracks and presents several advantages in order to distinguish between the various growth regimes. By choosing this growth geometry it is also possible to use without ambiguity the box-counting method to obtain the fractal dimension for different subsets of the patterns and for a wide range of the internal parameters of the model. We find a continuous dependence of the fractal dimension of the whole patterns and of their backbones on the ratio between the central- and noncentral-force contributions. For the chemical distance we find a one-dimensional behavior independent of the relevant parameters, which seems to be a common feature for fractal growth processes.
Guido Caldarelli
guido.caldarelli@imtlucca.it
Claudio Castellano
Alessandro Vespignani
2012-02-27T09:29:04Z
2012-02-27T09:29:04Z
http://eprints.imtlucca.it/id/eprint/1187
This item is in the repository with the URL: http://eprints.imtlucca.it/id/eprint/1187
2012-02-27T09:29:04Z
Fixed scale transformation for fracture growth processes governed by vectorial fields
We use the Fixed Scale Transformation (FST) approach to study the problem of fractal growth in fracture patterns generated by using the Born Model. The application of the method to this model is very complex because of the vectorial nature of the system considered. In particular, the implementation of this scheme requires a careful choice of the fracture path and the identification of the appropriate way to take into account screening effects. The good agreements of our results with computer simulations shows the validity and flexibility of the FST method which represents a general theoretical approach for the study of fractal patterns evolution.
Guido Caldarelli
guido.caldarelli@imtlucca.it
Alessandro Vespignani
Luciano Pietronero
2012-02-27T09:19:37Z
2012-02-27T09:19:37Z
http://eprints.imtlucca.it/id/eprint/1186
This item is in the repository with the URL: http://eprints.imtlucca.it/id/eprint/1186
2012-02-27T09:19:37Z
Fixed scale transformation approach for born model of fractures
We use the Fixed Scale Transformation theoretical approach to study the problem of fractal growth in fractures generated by using the Born Model. In this case the application of the method is more complex because of the vectorial nature of the model considered. In particular, one needs a careful choice of the lattice path integral for the fracture evolution and the identification of the appropriate way to take effectively into account screening effects. The good agreement of our results with computer simulations shows the validity and flexibility of the FST method in the study of fractal patterns evolution.
Guido Caldarelli
guido.caldarelli@imtlucca.it
Alessandro Vespignani
2012-02-27T09:08:26Z
2012-02-27T09:08:26Z
http://eprints.imtlucca.it/id/eprint/1185
This item is in the repository with the URL: http://eprints.imtlucca.it/id/eprint/1185
2012-02-27T09:08:26Z
Self-organized critical scaling at surfaces
At dissipative boundaries, models of self-organized criticality show peculiar scalings, different from the bulk ones, in the distributions characterizing avalanches. For Abelian models with Dirichlet boundary conditions, evidence of this is obtained by a mean field approach to semi-infinite sandpiles, and by numerical simulations in two and three dimensions. On the other hand, within the mean field description, closed Neumann conditions restore bulk scaling exponents also at the border. Numerical results are consistent with this property also at finite d.
Attilio Stella
Claudio Tebaldi
Guido Caldarelli
guido.caldarelli@imtlucca.it
2012-02-27T08:52:38Z
2012-02-27T08:52:38Z
http://eprints.imtlucca.it/id/eprint/1184
This item is in the repository with the URL: http://eprints.imtlucca.it/id/eprint/1184
2012-02-27T08:52:38Z
Quenched disorder, memory, and self-organization
We use a stochastic description of models with a dynamic in quenched disorder to analyze the mechanism of their self-organization to a critical state in terms of memory effects. We introduce a framework to characterize both memory effects and avalanche events which suggests that self-organization can result in general from memory. This issue is settled by the introduction and the analysis of a model that contains explicitly memory and generalizes the corresponding dynamics in quenched disorder. The model displays a rich behavior and self-organized critical properties for a whole range of the exponent that tunes the strength of memory.
Matteo Marsili
Guido Caldarelli
guido.caldarelli@imtlucca.it
Michele Vendruscolo
2012-02-27T08:49:31Z
2012-02-27T08:49:31Z
http://eprints.imtlucca.it/id/eprint/1183
This item is in the repository with the URL: http://eprints.imtlucca.it/id/eprint/1183
2012-02-27T08:49:31Z
Optimal path and directed percolation
An efficient transfer matrix technique is introduced to study directed optimal paths in two and three dimensions. The roughness exponent ζ is 0.6325±0.0007 for the two-dimensional case and ζ=0.555±0.008 for the three-dimensional one, in agreement with the recent conjecture ζ=ν⊥/ν∥, where ν⊥ and ν∥ are the correlation length exponents of directed percolation. Exactly solvable examples are also analyzed.
Paolo Rios
Guido Caldarelli
guido.caldarelli@imtlucca.it
Amos Maritan
Flavio Seno
2012-02-27T08:44:42Z
2014-12-05T09:47:55Z
http://eprints.imtlucca.it/id/eprint/1182
This item is in the repository with the URL: http://eprints.imtlucca.it/id/eprint/1182
2012-02-27T08:44:42Z
Branching processes and evolution at the ends of a food chain
In a critically self-organized model of punctuated equilibrium, boundaries determine peculiar scaling of the size distribution of evolutionary avalanches. This is derived by an inhomogeneous generalization of standard branching processes, extending previous mean field descriptions and yielding ν = 1/2 together with τ′ = 7/4, as distribution exponent of avalanches starting from species at the ends of a food chain. For the nearest neighbor chain one obtains numerically τ′ = 1.25±0.01, and τfirst′ = 1.35±0.01 for the first return times of activity, again distinct from bulk exponents.
Guido Caldarelli
guido.caldarelli@imtlucca.it
Claudio Tebaldi
Attilio Stella
2012-02-27T08:34:39Z
2014-12-05T09:46:23Z
http://eprints.imtlucca.it/id/eprint/1181
This item is in the repository with the URL: http://eprints.imtlucca.it/id/eprint/1181
2012-02-27T08:34:39Z
Self-organization and annealed disorder in a fracturing process
We show that a vectorial model for inhomogeneous elastic media self-organizes under external stress. An onset of crack avalanches of every duration and length scale compatible with the lattice size is observed. The behavior is driven by the introduction of annealed disorder, i.e., by lowering the breaking threshold in the neighborhood of a bond broken by the stress, with a process similar to self-organized criticality. A further comparison with experimental results of acoustic emission (AE), shows that the stability of the elastic potential energy of the system in the AE regime is a sufficient condition for reproducing the algebraic distribution of the energy released during cracks formation.
Guido Caldarelli
guido.caldarelli@imtlucca.it
Francesco Di Tolla
Alberto Petri
2012-02-24T13:48:37Z
2012-02-24T13:48:37Z
http://eprints.imtlucca.it/id/eprint/1179
This item is in the repository with the URL: http://eprints.imtlucca.it/id/eprint/1179
2012-02-24T13:48:37Z
Hot sandpiles
A temperature-like parameter is introduced in ordinary sandpiles models. A temperature-dependent probability distribution is assigned for the sand toppling on sites of any height. In mean-field theory criticality is obtained for all the values of temperature and no characteristic avalanche size appears. Numerical simulations support the existence of criticality at any temperature with apparently continuously varying critical exponents.
Guido Caldarelli
guido.caldarelli@imtlucca.it
Amos Maritan
Michele Vendruscolo
2012-02-24T13:39:36Z
2012-02-24T13:39:36Z
http://eprints.imtlucca.it/id/eprint/1178
This item is in the repository with the URL: http://eprints.imtlucca.it/id/eprint/1178
2012-02-24T13:39:36Z
Randomly pinned landscape evolution
A simple scheme for the evolution of a fluvial landscape in heterogeneous environments is critically examined to capture the essential mechanism responsible for the recurrent scale-free landforms in the river basin. It is shown that, regardless of boundary and initial conditions, geomorphological constraints in the form of quenched randomly pinned regions play a key role in the robust emergence of aggregation patterns with a scaling behavior in agreement with that of real river basins.
Guido Caldarelli
guido.caldarelli@imtlucca.it
Achille Giacometti
Amos Maritan
Ignacio Rodriguez-Iturbe
Andrea Rinaldo
2012-02-24T13:19:35Z
2012-02-27T15:00:59Z
http://eprints.imtlucca.it/id/eprint/1177
This item is in the repository with the URL: http://eprints.imtlucca.it/id/eprint/1177
2012-02-24T13:19:35Z
Surface effects in invasion percolation
Boundary effects for invasion percolation are introduced and discussed here. The presence of boundaries determines a set of critical exponents characteristic of the boundary. In this paper we present numerical simulations showing a remarkably different fractal dimension for the region of the percolating cluster near the boundary. In fact, near the surface we find a value of $D^{sur}=1.65\pm 0.02$,(for IP with trapping $D_{tr}^{sur}=1.59\pm 0.03$), compared with the bulk value of $D_{sur}=1.88\pm 0.02$ ($D_{tr}^{sur}=1.85\pm 0.02$). We ﬁnd a logarithmic
crossover from surface to bulk fractal properties, as one would expect from the ﬁnite-size theory
of critical systems. The distribution of the quenched variables on the growing interface near
the boundary self-organizes into an asymptotic shape characterized by a discontinuity at a value $x_c=0.5$, which coincides with the bulk critical threshold. The exponent $\tau^{sur}$ of the boundary
avalanche distribution for IP without trapping is $\tau^{sur}=1.56\pm 0.05$; this value is very near
to the bulk one. Then we conclude that only the geometrical properties (fractal dimension) of
the model are affected by the presence of a boundary, while other statistical and dynamical
properties are unchanged. Furthermore, we are able to present a theoretical computation of the
relevant critical exponents near the boundary. This analysis combines two recently introduced
theoretical tools, the ﬁxed scale transformation and the run time statistics, which are particularly
suited for the study of irreversible self-organized growth models with quenched disorder. Our
theoretical results are in rather good agreement with numerical data.
Raffaele Cafiero
Guido Caldarelli
guido.caldarelli@imtlucca.it
Andrea Gabrielli
2012-02-24T13:15:33Z
2012-02-24T13:15:33Z
http://eprints.imtlucca.it/id/eprint/1176
This item is in the repository with the URL: http://eprints.imtlucca.it/id/eprint/1176
2012-02-24T13:15:33Z
Scaling in currency exchange
We study the scaling behavior in currency exchange rates. Our results suggest that they satisfy scaling with an exponent close to 0.5, but that it differs qualitatively from that of a simple random walk. Indeed price variations cannot be considered as independent variables and subtle correlations are present. Furthermore, we introduce a novel statistical analysis for economic data which makes the physical properties of a signal more evident and eliminates the systematic effects of time periodicity.
Stefano Galluccio
Guido Caldarelli
guido.caldarelli@imtlucca.it
Matteo Marsili
Yi-Cheng Zhang
2012-02-24T13:11:10Z
2013-11-20T13:15:01Z
http://eprints.imtlucca.it/id/eprint/1175
This item is in the repository with the URL: http://eprints.imtlucca.it/id/eprint/1175
2012-02-24T13:11:10Z
A prototype model of stock exchange
A prototype model of stock market is introduced and studied numerically. In this self-organized system, we consider only the interaction among traders without external influences. Agents trade according to their own strategy, to accumulate their assets by speculating on the price's fluctuations which are produced by themselves. The model reproduced rather realistic price histories whose statistical properties are also similar to those observed in real markets.
Guido Caldarelli
guido.caldarelli@imtlucca.it
Matteo Marsili
Yi-Cheng Zhang
2012-02-24T13:05:00Z
2012-02-24T13:05:00Z
http://eprints.imtlucca.it/id/eprint/1174
This item is in the repository with the URL: http://eprints.imtlucca.it/id/eprint/1174
2012-02-24T13:05:00Z
Mean field theory for ordinary and hot sandpiles
A mean field theory is discussed for a sandpile model, a cellular automaton prototype of systems showing self-organized criticality. The previous formulation of the mean field does not take into account the dissipation effects that take place on boundaries. This gives rise to some inconsistencies that are eliminated by carefully considering the boundaries effects, as it is shown in this paper. We present here a revised version of the MF equations. The main result is that criticality arises in the thermodynamic limit for sandpile systems, confirming numerical observations on the behavior of the order parameter.
The mean field approach is also generalized by applying it to the more general case of sandpiles in thermal equilibrium where a temperature-like parameter T is introduced. In this case we show that criticality is not destroyed at T> 0.
Guido Caldarelli
guido.caldarelli@imtlucca.it
2012-02-24T13:00:55Z
2013-11-20T13:17:17Z
http://eprints.imtlucca.it/id/eprint/1173
This item is in the repository with the URL: http://eprints.imtlucca.it/id/eprint/1173
2012-02-24T13:00:55Z
Dynamics of fractures in quenched disordered media
We introduce a model for fractures in quenched disordered media. This model has a deterministic extremal dynamics, driven by the energy function of a network of springs (Born Hamiltonian). The breakdown is the result of the cooperation between the external field and the quenched disorder. This model can be considered as describing the low-temperature limit for crack propagation in solids. To describe the memory effects in this dynamics and then to study the resistance properties of the system we realized some numerical simulations of the model. The model exhibits interesting geometric and dynamical properties, with a strong reduction of the fractal dimension of the clusters and of their backbone, with respect to the case in which thermal fluctuations dominate. This result can be explained by a recently introduced theoretical tool as a screening enhancement due to memory effects induced by the quenched disorder.
Guido Caldarelli
guido.caldarelli@imtlucca.it
Raffaele Cafiero
Andrea Gabrielli
2012-02-24T12:56:03Z
2013-11-20T13:19:15Z
http://eprints.imtlucca.it/id/eprint/1172
This item is in the repository with the URL: http://eprints.imtlucca.it/id/eprint/1172
2012-02-24T12:56:03Z
Stationary self-organized fractal structures in an open, dissipative electrical system
We study the stationary state of a Poisson problem for a system of N perfectly conducting metal balls driven by electric forces to move within a medium of very low electrical conductivity onto which charges are sprayed from outside. When grounded at a confining boundary, the system of metal balls is experimentally known to self-organize into stable fractal aggregates. We simulate the dynamical conditions leading to the formation of such aggregated patterns and analyse the fractal properties. From our results and those obtained for steady-state systems that obey minimum total energy dissipation (and potential energy of the system as a whole), we suggest a possible dynamical rule for the emergence of scale-free structures in nature.
Marco Marani
Jayanth R Banavar
Guido Caldarelli
guido.caldarelli@imtlucca.it
Amos Maritan
Andrea Rinaldo
2012-02-24T12:50:55Z
2013-11-20T13:16:24Z
http://eprints.imtlucca.it/id/eprint/1171
This item is in the repository with the URL: http://eprints.imtlucca.it/id/eprint/1171
2012-02-24T12:50:55Z
Modelling coevolution in multispecies communities
We introduce the Webworld model, which links together the ecological modelling of food web structure with the evolutionary modelling of speciation and extinction events. The model describes dynamics of ecological communities on an evolutionary time-scale. Species are defined as sets of characteristic features, and these features are used to determine interaction scores between species. A simple rule is used to transfer resources from the external environment through the food web to each of the species, and to determine mean population sizes. A time step in the model represents a speciation event. A new species is added with features similar to those of one of the existing species and a new food web structure is than calculated. The new species may (i) add stably to the web, (ii) become extinct immediately because it is poorly adapted, or (iii) cause one or more other species to become extinct due to competition for resources.
We measure various properties of the model webs and compare these with data on real food webs. These properties include the proportions of basal, intermediate and top species, the number of links per species and the number of trophic levels. We also study the evolutionary dynamics of the model ecosystem by following the fluctuations in the total number of species in the web. Extinction avalanches occur when novel organisms arise which are significantly better adapted than existing ones. We discuss these results in relation to the observed extinction events in the fossil record, and to the theory of self-organized criticality.
Guido Caldarelli
guido.caldarelli@imtlucca.it
Paul G. Higgs
Alan J. McKane
2012-02-24T12:07:20Z
2013-11-20T13:28:33Z
http://eprints.imtlucca.it/id/eprint/1170
This item is in the repository with the URL: http://eprints.imtlucca.it/id/eprint/1170
2012-02-24T12:07:20Z
Theory of boundary effects in invasion percolation
We study the boundary effects in invasion percolation (IP) with and without trapping. We find that the presence of boundaries introduces a new set of surface critical exponents, as in the case of standard percolation. Numerical simulations show a fractal dimension, for the region of the percolating cluster near the boundary, remarkably different from the bulk one. In fact, on the surface we find a value of (for IP with trapping ), compared with the bulk value of . We find a logarithmic crossover from surface to bulk fractal properties, as one would expect from the finite-size theory of critical systems. The distribution of the quenched variables on the growing interface near the boundary self-organizes into an asymptotic shape characterized by a discontinuity at a value , which coincides with the bulk critical threshold. The exponent of the boundary avalanche distribution for IP without trapping is ; this value is very near to the bulk one. Then we conclude that only the geometrical properties (fractal dimension) of the model are affected by the presence of a boundary, while other statistical and dynamical properties are unchanged. Furthermore, we are able to present a theoretical computation of the relevant critical exponents near the boundary. This analysis combines two recently introduced theoretical tools, the fixed scale transformation and the run time statistics, which are particularly suited for the study of irreversible self-organized growth models with quenched disorder. Our theoretical results are in rather good agreement with numerical data.
Andrea Gabrielli
Raffaele Cafiero
Guido Caldarelli
guido.caldarelli@imtlucca.it
2012-02-24T11:30:08Z
2013-11-20T13:30:21Z
http://eprints.imtlucca.it/id/eprint/1169
This item is in the repository with the URL: http://eprints.imtlucca.it/id/eprint/1169
2012-02-24T11:30:08Z
Statistical properties of fractures in damaged materials
We introduce a model for the dynamics of mud cracking in the limit of of extremely thin layers. In this model the growth of fracture proceeds by selecting the part of the material with the smallest (quenched) breaking threshold. In addition, weakening affects the area of the sample neighbour to the crack. Due to the simplicity of the model, it is possible to derive some analytical results. In particular, we find that the total time to break down the sample grows with the dimension L of the lattice as L2 even though the percolating cluster has a non-trivial fractal dimension. Furthermore, we obtain a formula for the mean weakening with time of the whole sample.
Andrea Gabrielli
Raffaele Cafiero
Guido Caldarelli
guido.caldarelli@imtlucca.it
2012-02-24T11:25:05Z
2014-12-05T09:42:48Z
http://eprints.imtlucca.it/id/eprint/1168
This item is in the repository with the URL: http://eprints.imtlucca.it/id/eprint/1168
2012-02-24T11:25:05Z
Comment on “First-Order Transition in the Breakdown of Disordered Media”
Guido Caldarelli
guido.caldarelli@imtlucca.it
Alberto Petri
2012-02-24T11:21:03Z
2012-02-24T11:21:03Z
http://eprints.imtlucca.it/id/eprint/1167
This item is in the repository with the URL: http://eprints.imtlucca.it/id/eprint/1167
2012-02-24T11:21:03Z
Criticality in models for fracture in disordered media
It has been recently noticed that heterogeneous media undergoing a fracturing process display a set of properties characteristic of systems at the critical state. In the present work we focus on the way in which the critical regime is reached. It is possible to define a branching ratio, for the breaking processses in the material, that represents the probability to trigger future breakdowns given an initial failure. This probability takes the value 1 when the system is critical thereby representing a measure of the distance of the system from the critical state. We show that, although the models considered in literature become really critical only in correspondence of the global failure, different dynamical rules may drive the system close to the critical state at different rates, such that the duration of the “quasi-critical” stage largely varies from model to model.
Guido Caldarelli
guido.caldarelli@imtlucca.it
Claudio Castellano
Alberto Petri
2012-02-24T11:11:55Z
2012-02-24T11:11:55Z
http://eprints.imtlucca.it/id/eprint/1166
This item is in the repository with the URL: http://eprints.imtlucca.it/id/eprint/1166
2012-02-24T11:11:55Z
Critical behaviour in the fracture of disordered media
Abstract In this paper we investigate the influence of different boundary conditions on the final breakdown of a lattice model for the fracture of heterogeneous media. Experimental evidence shows that disordered media subject to stress display some features that are characteristic of critical systems, therefore suggesting an interpretation of the global breakdown of the system as a kind of critical transition. Many of the observed features are well reproduced at least at a qualitative level by lattice models; however, mechanisms at the base of the onset of criticality are not well understood. Besides disorder, there are many parameters that seem to influence the critical properties of the system. The system size and the boundary conditions are among these. We find that the statistical properties of the final breakdown are strongly influenced by the boundary condition. In particular constant-stress relaxation leads to a final breakdown always involving the breaking of a finite number of bonds, which is also large if compared with the number of bonds broken during the formation of each localized crack preceding the final breakdown. When the lattice undergoes constant-strain relaxation instead, the breakdown may involve a vanishingly smali number of bond-breaking events.
Guido Caldarelli
guido.caldarelli@imtlucca.it
Claudio Castellano
Alberto Petri
2012-02-24T10:49:38Z
2013-11-20T14:02:02Z
http://eprints.imtlucca.it/id/eprint/1165
This item is in the repository with the URL: http://eprints.imtlucca.it/id/eprint/1165
2012-02-24T10:49:38Z
Roughness of fracture surfaces
We study the roughness of fracture surfaces of three-dimensional samples through numerical simulations of a model for quasi-static cracks known as Born Model. We find for the roughness exponent a value ζ simeq 0.5 measured for "small length scales" in microfracturing experiments. Our simulations confirm that at small length scales the fracture can be considered as quasi-static. The isotropy of the roughness exponent on the crack surface is also showed. Finally, considering the crack front, we compute the roughness exponents of longitudinal and transverse fluctuations of the crack line (ζpar ~ ζ⊥ ~ 0.5). They result in agreement with experimental data, and support the possible application of the model of line depinning in the case of long-range interactions.
Andrea Parisi
Guido Caldarelli
guido.caldarelli@imtlucca.it
Luciano Pietronero
2012-02-24T10:07:42Z
2013-11-20T14:03:52Z
http://eprints.imtlucca.it/id/eprint/1164
This item is in the repository with the URL: http://eprints.imtlucca.it/id/eprint/1164
2012-02-24T10:07:42Z
The fractal properties of Internet
In this paper we show that the Internet web, from a user's perspective, manifests robust scaling properties of the type P(n) propto n−τ, where n is the size of the basin connected to a given point, P represents the density of probability of finding n points downhill and τ = 1.9 ± 0.1 s a characteristic universal exponent. This scale-free structure is a result of the spontaneous growth of the web, but is not necessarily the optimal one for efficient transport. We introduce an appropriate figure of merit and suggest that a planning of few big links, acting as information highways, may noticeably increase the efficiency of the net without affecting its robustness.
Guido Caldarelli
guido.caldarelli@imtlucca.it
Riccardo Marchetti
Luciano Pietronero
2012-02-24T09:50:48Z
2014-12-05T09:37:29Z
http://eprints.imtlucca.it/id/eprint/1163
This item is in the repository with the URL: http://eprints.imtlucca.it/id/eprint/1163
2012-02-24T09:50:48Z
Discretized diffusion processes
We study the properties of the “rigid Laplacian” operator; that is we consider solutions of the Laplacian equation in the presence of fixed truncation errors. The dynamics of convergence to the correct analytical solution displays the presence of a metastable set of numerical solutions, whose presence can be related to granularity. We provide some scaling analysis in order to determine the value of the exponents characterizing the process. We believe that this prototype model is also suitable to provide an explanation of the widespread presence of power law in a social and economic system where information and decision diffuse, with errors and delay from agent to agent.
Stefano Ciliberti
Guido Caldarelli
guido.caldarelli@imtlucca.it
Paolo De Los Rios
Luciano Pietronero
Yi-Cheng Zhang
2012-02-24T09:39:55Z
2012-02-24T09:39:55Z
http://eprints.imtlucca.it/id/eprint/1161
This item is in the repository with the URL: http://eprints.imtlucca.it/id/eprint/1161
2012-02-24T09:39:55Z
Self-affine properties of fractures in brittle materials
We present the result of numerical simulations for a fracturing process in a three-dimensional solid subjected to a mode-I load in a quasi-static regime. The solid is described using the Born model on an FCC lattice with a starting notch. We obtain a value of the roughness exponent ζ≃0.5 in agreement with the value measured in microfracturing experiments. Our result supports the idea that at small length scales the fracturing process can be considered as quasi-static, which is the basic of the possible application of the model of line depinning to the case of fractures.
Andrea Parisi
Guido Caldarelli
guido.caldarelli@imtlucca.it
2012-02-23T11:26:35Z
2014-12-05T09:35:17Z
http://eprints.imtlucca.it/id/eprint/1160
This item is in the repository with the URL: http://eprints.imtlucca.it/id/eprint/1160
2012-02-23T11:26:35Z
Angular structure of lacunarity, and the renormalization group
We formulate the angular structure of lacunarity in fractals, in terms of a symmetry reduction of the three point correlation function. This provides a rich probe of universality, and first measurements yield new evidence in support of the equivalence between self-avoiding walks (SAW's) and percolation perimeters in two dimensions. We argue that the lacunarity reveals much of the renormalization group in real space. This is supported by exact calculations for random walks and measured data for percolation clusters and SAW's. Relationships follow between exponents governing inward and outward propagating perturbations, and we also find a very general test for the contribution of long-range interactions.
Robin C. Ball
Guido Caldarelli
guido.caldarelli@imtlucca.it
Alessandro Flammini
2012-02-23T11:15:18Z
2013-11-20T14:01:16Z
http://eprints.imtlucca.it/id/eprint/1159
This item is in the repository with the URL: http://eprints.imtlucca.it/id/eprint/1159
2012-02-23T11:15:18Z
Damage and cracking in thin mud layers
We present a detailed study of a two-dimensional lattice model introduced to describe mud cracking in the limit of extremely thin layers. In this model to each bond in the lattice is assigned a (quenched) random breaking threshold. Fractures proceed by selecting the `weakest' part of the material (i.e. the smallest value of the threshold). A local damage rule is also implemented, by using two different types of weakening of the neighbouring sites, corresponding to different physical situations. We present the results of numerical simulations on this model. We also derive some analytical results through a probabilistic approach known as run time statistics. In particular, we find that the total time to divide the sample scales with the square power L2 of the linear size L of the lattice. This result is not straightforward since the percolating cluster has a non-trivial fractal dimension. Furthermore, we present here a formula for the mean weakening of the whole sample during the evolution.
Raffaele Cafiero
Guido Caldarelli
guido.caldarelli@imtlucca.it
Andrea Gabrielli
2012-02-23T10:47:10Z
2013-11-20T13:59:43Z
http://eprints.imtlucca.it/id/eprint/1157
This item is in the repository with the URL: http://eprints.imtlucca.it/id/eprint/1157
2012-02-23T10:47:10Z
Invasion percolation with temperature and the nature of self-organized criticality in real systems
In this paper we present a theoretical approach that allows us to describe the transition between critical and noncritical behavior when stocastic noise is introduced in extremal models with disorder. Namely, we show that the introduction of thermal noise in invasion percolation (IP) brings the system outside the critical point. This result suggests a possible definition of self-organized criticality systems as ordinary critical systems where the critical point corresponds to set to 0 one of the parameters. We recover both the IP and Eden models for T⃗0 and T⃗∞, respectively. For small T we find a dynamical second-order transition with correlation length diverging when T⃗0.
Andrea Gabrielli
Guido Caldarelli
guido.caldarelli@imtlucca.it
Luciano Pietronero
2012-02-23T10:19:33Z
2013-11-20T14:16:49Z
http://eprints.imtlucca.it/id/eprint/1156
This item is in the repository with the URL: http://eprints.imtlucca.it/id/eprint/1156
2012-02-23T10:19:33Z
Putting proteins back into water
We introduce a simplified protein model where the solvent (water) degrees of freedom appear explicitly (although in an extremely simplified fashion). Using this model we are able to recover the thermodynamic phenomenology of proteins over a wide range of temperatures. In particular we describe both the warm and the cold protein denaturation within a single framework, while addressing important issues about the structure of model proteins.
Paolo De Los Rios
Guido Caldarelli
guido.caldarelli@imtlucca.it
2012-02-23T10:16:47Z
2013-11-20T14:18:23Z
http://eprints.imtlucca.it/id/eprint/1155
This item is in the repository with the URL: http://eprints.imtlucca.it/id/eprint/1155
2012-02-23T10:16:47Z
Cellular models for river networks
A cellular model introduced for the evolution of the fluvial landscape is revisited using extensive numerical and scaling analyses. The basic network shapes and their recurrence especially in the aggregation structure are then addressed. The roles of boundary and initial conditions are carefully analyzed as well as the key effect of quenched disorder embedded in random pinning of the landscape surface. It is found that the above features strongly affect the scaling behavior of key morphological quantities. In particular, we conclude that randomly pinned regions (whose structural disorder bears much physical meaning mimicking uneven landscape-forming rainfall events, geological diversity or heterogeneity in surficial properties like vegetation, soil cover or type) play a key role for the robust emergence of aggregation patterns bearing much resemblance to real river networks.
Guido Caldarelli
guido.caldarelli@imtlucca.it
2012-02-23T10:12:18Z
2012-02-23T10:12:18Z
http://eprints.imtlucca.it/id/eprint/1154
This item is in the repository with the URL: http://eprints.imtlucca.it/id/eprint/1154
2012-02-23T10:12:18Z
Cold and warm swelling of hydrophobic polymers
We introduce a polymer model where the transition from swollen to compact configurations is due to interactions between the monomers and the solvent. These interactions are the origin of the effective attractive interactions between hydrophobic amino acids in proteins. We find that in the low and high temperature phases polymers are swollen, and there is an intermediate phase where the most favorable configurations are compact. We argue that such a model captures in a single framework both the cold and the warm denaturation experimentally detected for thermosensitive polymers and for proteins.
Paolo De Los Rios
Guido Caldarelli
guido.caldarelli@imtlucca.it
2012-02-23T10:07:06Z
2012-02-23T10:07:06Z
http://eprints.imtlucca.it/id/eprint/1153
This item is in the repository with the URL: http://eprints.imtlucca.it/id/eprint/1153
2012-02-23T10:07:06Z
Sex-oriented stable matchings of the marriage problem with correlated and incomplete information
In the stable marriage problem two sets of agents must be paired according to mutual preferences, which may happen to conflict. We present two generalizations of its sex-oriented version, aiming to take into account correlations between the preferences of agents and costly information. Their effects are investigated both numerically and analytically.
Guido Caldarelli
guido.caldarelli@imtlucca.it
Andrea Capocci
Paolo Laureti
2012-02-22T16:33:38Z
2013-11-20T14:03:00Z
http://eprints.imtlucca.it/id/eprint/1152
This item is in the repository with the URL: http://eprints.imtlucca.it/id/eprint/1152
2012-02-22T16:33:38Z
Beauty and distance in the stable marriage problem
The stable marriage problem has been introduced in order to describe a complex system where individuals attempt to optimise their own satisfaction, subject to mutually conflicting constraints. Due to the potential large applicability of such model to describe all the situation where different objects has to be matched pairwise, the statistical properties of this model have been extensively studied. In this paper, we present a generalisation of this model, introduced in order to take into account the presence of correlations in the lists and the effects of distance when the players are supposed to be represented by a position in space.
Guido Caldarelli
guido.caldarelli@imtlucca.it
Andrea Capocci
2012-02-22T16:18:26Z
2014-12-05T09:31:58Z
http://eprints.imtlucca.it/id/eprint/1151
This item is in the repository with the URL: http://eprints.imtlucca.it/id/eprint/1151
2012-02-22T16:18:26Z
Perturbative approach to the Bak-Sneppen model
We study the Bak-Sneppen model in the probabilistic framework of the run time statistics (RTS). This model has attracted a large interest for its simplicity being a prototype for the whole class of models showing self-organized criticality. The dynamics is characterized by a self-organization of almost all the species fitnesses above a nontrivial threshold value, and by a lack of spatial and temporal characteristic scales. This results in avalanches of activity power law distributed. In this Letter we use the RTS approach to compute the value of xc, the value of the avalanche exponent τ, and the asymptotic distribution of minimal fitnesses.
Maddalena Felici
Guido Caldarelli
guido.caldarelli@imtlucca.it
Andrea Gabrielli
Luciano Pietronero
2012-02-22T10:59:34Z
2012-02-22T10:59:34Z
http://eprints.imtlucca.it/id/eprint/1145
This item is in the repository with the URL: http://eprints.imtlucca.it/id/eprint/1145
2012-02-22T10:59:34Z
Growing dynamics of Internet providers
In this paper we present a model for the growth and evolution of Internet providers. The model reproduces the data observed for the Internet connection as probed by tracing routes from different computers. This problem represents a paramount case of study for growth processes in general, but can also help in the understanding the properties of the Internet. Our main result is that this network can be reproduced by a self-organized interaction between users and providers that can rearrange in time. This model can then be considered as a prototype model for the class of phenomena of aggregation processes in social networks.
Andrea Capocci
Guido Caldarelli
guido.caldarelli@imtlucca.it
Riccardo Marchetti
Luciano Pietronero
2012-02-22T10:36:35Z
2013-11-20T14:15:03Z
http://eprints.imtlucca.it/id/eprint/1144
This item is in the repository with the URL: http://eprints.imtlucca.it/id/eprint/1144
2012-02-22T10:36:35Z
Fractal growth from local instabilities
We study, both with numerical simulations and theoretical methods, a cellular automata model for surface growth in the presence of a local instability, driven by an external flux of particles. The growing tip is selected with probability proportional to the local curvature. A probability p of developing overhangs through lateral growth is also introduced. For small external fluxes, we find a fractal regime of growth. The value of p determines the fractal dimension of the aggregate. Furthermore, for each value of p a crossover between two different fractal dimensions is observed. The roughness exponent χ of the aggregates, instead, does not depend on p (χ simeq 0.5). A Fixed Scale Transformation (FST) approach is applied to compute theoretically the fractal dimension for one of the branches of the structure.
Raffaele Cafiero
Guido Caldarelli
guido.caldarelli@imtlucca.it
2012-02-21T13:36:05Z
2013-11-20T14:23:53Z
http://eprints.imtlucca.it/id/eprint/1143
This item is in the repository with the URL: http://eprints.imtlucca.it/id/eprint/1143
2012-02-21T13:36:05Z
Percolation in real wildfires
This paper focuses on the statistical properties of wild-land fires and, in particular, investigates if spread dynamics relates to simple invasion model. The fractal dimension and lacunarity of three fire scars classified from satellite imagery are analysed. Results indicate that the burned clusters behave similarly to percolation clusters on boundaries and look denser in their core. We show that Dynamical Percolation reproduces this behaviour and can help to describe the fire evolution. By mapping fire dynamics onto the percolation models, the strategies for fire control might be improved.
Guido Caldarelli
guido.caldarelli@imtlucca.it
Raffaella Frondoni
Andrea Gabrielli
Marco Montuori
Rebecca Retzlaff
Carlo Ricotta
2012-02-21T13:08:49Z
2013-11-20T14:27:32Z
http://eprints.imtlucca.it/id/eprint/1142
This item is in the repository with the URL: http://eprints.imtlucca.it/id/eprint/1142
2012-02-21T13:08:49Z
Cold and warm denaturation of proteins
We introduce a simplified protein model where the water degrees of freedom appear explicitly (although in an extremely simplified fashion). Using this model we are able to recover both the warm and the cold protein denaturation within a single framework, while addressing important issues about the structure of model proteins.
Guido Caldarelli
guido.caldarelli@imtlucca.it
Paolo De Los Rios
2012-02-21T12:03:48Z
2012-02-21T14:06:17Z
http://eprints.imtlucca.it/id/eprint/1140
This item is in the repository with the URL: http://eprints.imtlucca.it/id/eprint/1140
2012-02-21T12:03:48Z
Probabilistic approach to the Bak-Sneppen model
We study here the Bak-Sneppen model, a prototype model for the study of self-organized criticality. In this model several species interact and undergo extinction with a power-law distribution of activity bursts. Species are defined through their “fitness” whose distribution in the system is uniform above a certain threshold. Run time statistics is introduced for the analysis of the dynamics in order to explain the peculiar properties of the model. This approach based on conditional probability theory, takes into account the correlations due to memory effects. In this way, we may compute analytically the value of the fitness threshold with the desired precision. This represents a substantial improvement with respect to the traditional mean field approach.
Guido Caldarelli
guido.caldarelli@imtlucca.it
Maddalena Felici
Andrea Gabrielli
Luciano Pietronero
2012-02-21T11:53:24Z
2012-02-21T14:07:19Z
http://eprints.imtlucca.it/id/eprint/1139
This item is in the repository with the URL: http://eprints.imtlucca.it/id/eprint/1139
2012-02-21T11:53:24Z
Local rigidity in sandpile models
We address the problem of the role of the concept of local rigidity in the family of sandpile systems. We define rigidity as the ratio between the critical energy and the amplitude of the external perturbation and we show, in the framework of the dynamically driven renormalization group, that any finite value of the rigidity in a generalized sandpile model renormalizes to an infinite value at the fixed point, i.e., on a large scale. The fixed-point value of the rigidity allows then for a nonambiguous distinction between sandpilelike systems and diffusive systems. Numerical simulations support our analytical results.
Stefano Ciliberti
Guido Caldarelli
guido.caldarelli@imtlucca.it
Vittorio Loreto
Luciano Pietronero
2012-02-21T11:14:52Z
2012-02-21T11:16:19Z
http://eprints.imtlucca.it/id/eprint/1138
This item is in the repository with the URL: http://eprints.imtlucca.it/id/eprint/1138
2012-02-21T11:14:52Z
Reply to the Comment by H. Tephany and J. Nahmias on “Percolation in real wildfires” by G. Caldarelli et al.
Guido Caldarelli
guido.caldarelli@imtlucca.it
Raffaella Frondoni
Andrea Gabrielli
Marco Montuori
Rebecca Retzlaff
Carlo Ricotta
2012-02-21T10:52:51Z
2014-12-05T09:27:10Z
http://eprints.imtlucca.it/id/eprint/1137
This item is in the repository with the URL: http://eprints.imtlucca.it/id/eprint/1137
2012-02-21T10:52:51Z
Scale-Free networks from varying vertex intrinsic fitness
A new mechanism leading to scale-free networks is proposed in this Letter. It is shown that, in many cases of interest, the connectivity power-law behavior is neither related to dynamical properties nor to preferential attachment. Assigning a quenched fitness value xi to every vertex, and drawing links among vertices with a probability depending on the fitnesses of the two involved sites, gives rise to what we call a good-get-richer mechanism, in which sites with larger fitness are more likely to become hubs (i.e., to be highly connected).
Guido Caldarelli
guido.caldarelli@imtlucca.it
Andrea Capocci
Paolo De Los Rios
Miguel A. Muñoz
2012-02-21T10:37:14Z
2012-02-27T10:37:03Z
http://eprints.imtlucca.it/id/eprint/1136
This item is in the repository with the URL: http://eprints.imtlucca.it/id/eprint/1136
2012-02-21T10:37:14Z
Multi-layer model for the web graph
This paper studies stochastic graph models of the WebGraph. We present a new model that describes the WebGraph as an ensemble of different regions generated by independent stochastic processes (in the spirit of a recent paper by Dill et al. [VLDB 2001]). Models such as the Copying Model [17] and Evolving Networks Model [3] are simulated and compared on several relevant measures such as degree and clique distribution.
Luigi Laura
Stefano Leonardi
Guido Caldarelli
guido.caldarelli@imtlucca.it
Paolo De Los Rios
2012-02-20T13:54:38Z
2018-03-08T17:08:28Z
http://eprints.imtlucca.it/id/eprint/1135
This item is in the repository with the URL: http://eprints.imtlucca.it/id/eprint/1135
2012-02-20T13:54:38Z
Universal scaling relations in food webs
The structure of ecological communities is usually represented by food webs. In these webs, we describe species by means of vertices connected by links representing the predations. We can therefore study different webs by considering the shape (topology) of these networks. Comparing food webs by searching for regularities is of fundamental importance, because universal patterns would reveal common principles underlying the organization of different ecosystems. However, features observed in small food webs are different from those found in large ones. Furthermore, food webs (except in isolated cases) do not share general features with other types of network (including the Internet, the World Wide Web and biological webs). These features are a small-world character and a scale-free (power-law) distribution of the degree (the number of links per vertex). Here we propose to describe food webs as transportation networks by extending to them the concept of allometric scaling (how branching properties change with network size). We then decompose food webs in spanning trees and loop-forming links. We show that, whereas the number of loops varies significantly across real webs, spanning trees are characterized by universal scaling relations.
Diego Garlaschelli
diego.garlaschelli@imtlucca.it
Guido Caldarelli
guido.caldarelli@imtlucca.it
Luciano Pietronero
2012-02-20T13:43:10Z
2013-11-20T14:30:41Z
http://eprints.imtlucca.it/id/eprint/1134
This item is in the repository with the URL: http://eprints.imtlucca.it/id/eprint/1134
2012-02-20T13:43:10Z
Topology of correlation-based minimal spanning trees in real and model markets
We compare the topological properties of the minimal spanning tree obtained from a large group of stocks traded at the New York Stock Exchange during a 12-year trading period with the one obtained from surrogated data simulated by using simple market models. We find that the empirical tree has features of a complex network that cannot be reproduced, even as a first approximation, by a random market model and by the widespread one-factor model.
Giovanni Bonanno
Guido Caldarelli
guido.caldarelli@imtlucca.it
Fabrizio Lillo
Rosario Nunzio Mantegna
2012-02-20T13:38:39Z
2018-03-08T17:08:41Z
http://eprints.imtlucca.it/id/eprint/1133
This item is in the repository with the URL: http://eprints.imtlucca.it/id/eprint/1133
2012-02-20T13:38:39Z
Food web structure and the evolution of complex networks
In addition to traditional properties such as the degree distribution P(k), in this work we propose two other useful quantities that can help in characterizing the topology of food webs quantitatively, namely the allometric scaling relations C(A) and the branch size distribution P(A) which are defined on the spanning tree of the webs. These quantities, whose use has proved relevant in characterizing other different networks appearing in nature (such as river basins, Internet, and vascular systems), are related (in the context of food webs) to the efficiency in the resource transfer and to the stability against species removal. We present the analysis of the data for both real food webs and numerical simulations of a growing network model. Our results allow us to conclude that real food webs display a high degree of both efficiency and stability due to the evolving character of their topology.
Guido Caldarelli
guido.caldarelli@imtlucca.it
Diego Garlaschelli
diego.garlaschelli@imtlucca.it
Luciano Pietronero
2012-02-15T16:25:31Z
2012-02-21T13:54:41Z
http://eprints.imtlucca.it/id/eprint/1130
This item is in the repository with the URL: http://eprints.imtlucca.it/id/eprint/1130
2012-02-15T16:25:31Z
Quantitative description and modeling of real networks
We present data analysis and modeling of two particular cases of study in the field of growing networks. We analyze World Wide Web data set and authorship collaboration networks in order to check the presence of correlation in the data. The results are reproduced with good agreement through a suitable modification of the standard Albert-Barabási model of network growth. In particular, intrinsic relevance of sites plays a role in determining the future degree of the vertex.
Andrea Capocci
Guido Caldarelli
guido.caldarelli@imtlucca.it
Paolo De Los Rios
2012-02-15T16:22:57Z
2013-11-20T14:28:27Z
http://eprints.imtlucca.it/id/eprint/1129
This item is in the repository with the URL: http://eprints.imtlucca.it/id/eprint/1129
2012-02-15T16:22:57Z
Dynamic fracture model for acoustic emission
We study the acoustic emission produced by micro-cracks using a two-dimensional disordered lattice model of dynamic fracture, which allows to relate the acoustic response to the internal damage of the sample. We find that the distributions of acoustic energy bursts decays as a power law in agreement with experimental observations. The scaling exponents measured in the present dynamic model can related to those obtained in the quasi-static random fuse model.
Manuela Minozzi
Guido Caldarelli
guido.caldarelli@imtlucca.it
Luciano Pietronero
Stefano Zapperi
2012-02-15T16:12:41Z
2013-11-21T09:02:22Z
http://eprints.imtlucca.it/id/eprint/1128
This item is in the repository with the URL: http://eprints.imtlucca.it/id/eprint/1128
2012-02-15T16:12:41Z
Widespread occurrence of the inverse square distribution in social sciences and taxonomy
The widespread occurrence of an inverse square relation in the hierarchical distribution of subcommunities within communities (or subspecies within species) has been recently invoked as a signature of hierarchical self-organization within social and ecological systems. Here we show that, whether such systems are self-organized or not, this behavior is the consequence of the treelike classification method. Different treelike classifications (both of real and truly random systems) display a similar statistical behavior when considering the sizes of their sub-branches.
Guido Caldarelli
guido.caldarelli@imtlucca.it
Cécile Caretta Cartozo
Paolo De Los Rios
Vito D. P. Servedio
2012-02-15T16:02:44Z
2012-02-15T16:02:44Z
http://eprints.imtlucca.it/id/eprint/1127
This item is in the repository with the URL: http://eprints.imtlucca.it/id/eprint/1127
2012-02-15T16:02:44Z
Structure of cycles and local ordering in complex networks
We study the properties of quantities aimed at the characterization of grid-like ordering in complex networks. These quantities are based on the global and local behavior of cycles of order four, which are the minimal structures able to identify rectangular clustering. The analysis of data from real networks reveals the ubiquitous presence of a statistically high level of grid-like ordering that is non-trivially correlated with the local degree properties. These observations provide new insights on the hierarchical structure of complex networks.
Guido Caldarelli
guido.caldarelli@imtlucca.it
Romualdo Pastor-Satorras
Alessandro Vespignani
2012-02-15T15:54:46Z
2012-02-15T15:54:46Z
http://eprints.imtlucca.it/id/eprint/1126
This item is in the repository with the URL: http://eprints.imtlucca.it/id/eprint/1126
2012-02-15T15:54:46Z
Preface on "Applications of Networks"
Guido Caldarelli
guido.caldarelli@imtlucca.it
Ayşe Erzan
Alessandro Vespignani
2012-02-15T15:49:49Z
2012-02-15T15:49:49Z
http://eprints.imtlucca.it/id/eprint/1125
This item is in the repository with the URL: http://eprints.imtlucca.it/id/eprint/1125
2012-02-15T15:49:49Z
Virtual Round Table on ten leading questions for network research
The following discussion is an edited summary of the public debate started during the conference "Growing Networks and Graphs in Statistical Physics, Finance, Biology and Social Systems" held in Rome in September 2003. Drafts documents were circulated electronically among experts in the field and additions and follow-up to the original discussion have been included. Among the scientists participating to the discussion L.A.N. Amaral, A. Barrat, A.L. Barabasi, G. Caldarelli, P. De Los Rios, A. Erzan, B. Kahng, R. Mantegna, J.F.F. Mendes, R. Pastor-Satorras, A. Vespignani are acknowledged for their contributions and editing.
Luis A. N. Amaral
Alain Barrat
Guido Caldarelli
guido.caldarelli@imtlucca.it
Albert-László Barabási
Paolo De Los Rios
Ayşe Erzan
Byungnam Kahng
Rosario Nunzio Mantegna
Josè F. F. Mendes
Romualdo Pastor-Satorras
Alessandro Vespignani
2012-02-15T15:33:23Z
2012-02-15T15:33:23Z
http://eprints.imtlucca.it/id/eprint/1124
This item is in the repository with the URL: http://eprints.imtlucca.it/id/eprint/1124
2012-02-15T15:33:23Z
Networks of equities in financial markets
We review the recent approach of correlation based networks of financial equities. We investigate portfolio of stocks at different time horizons, financial indices and volatility time series and we show that meaningful economic information can be extracted from noise dressed correlation matrices. We show that the method can be used to falsify widespread market models by directly comparing the topological properties of networks of real and artificial markets.
Giovanni Bonanno
Guido Caldarelli
guido.caldarelli@imtlucca.it
Fabrizio Lillo
Salvatore Miccichè
Nicolas Vandewalle
Rosario Nunzio Mantegna
2012-02-15T14:23:12Z
2012-02-15T14:23:12Z
http://eprints.imtlucca.it/id/eprint/1123
This item is in the repository with the URL: http://eprints.imtlucca.it/id/eprint/1123
2012-02-15T14:23:12Z
Statistical features of drainage basins in mars channel networks: can one guess from the landscape the past presence of water?
Erosion by flowing water is one of the major forces shaping the surface of Earth. Studies in the last decade have shown, in particular, that the drainage region of rivers, where water is collected, exhibits scale invariant features characterized by exponents that are the same for rivers around the world. Here we show that from the data obtained by the MOLA altimeter of the Mars Global Surveyor one can perform the same analysis for mountain sides on Mars. We then show that in some regions fluid erosion might have played a role in the present martian landscape.
Guido Caldarelli
guido.caldarelli@imtlucca.it
Paolo De Los Rios
Marco Montuori
Vito D. P. Servedio
2012-02-14T14:36:31Z
2013-11-21T09:03:40Z
http://eprints.imtlucca.it/id/eprint/1121
This item is in the repository with the URL: http://eprints.imtlucca.it/id/eprint/1121
2012-02-14T14:36:31Z
Preferential exchange: strengthening connections in complex networks
Many social, technological, and biological interactions involve network relationships whose outcome intimately depends on the structure of the network and on the strengths of the connections. Yet, although much information is now available concerning the structure of many networks, the strengths are more difficult to measure. Here we show that, for one particular social network, notably the e-mail network, a suitable measure of the strength of the connections can be available. We also propose a simple mechanism, based on positive feedback and reciprocity, that can explain the observed behavior and that hints toward specific dynamics of formation and reinforcement of network connections. Network data from contexts different from social sciences indicate that power-law, and generally broad, distributions of the connection strength are ubiquitous, and the proposed mechanism has a wide range of applicability.
Guido Caldarelli
guido.caldarelli@imtlucca.it
Fabrizio Coccetti
Paolo De Los Rios
2012-02-14T14:31:41Z
2013-11-20T14:32:59Z
http://eprints.imtlucca.it/id/eprint/1120
This item is in the repository with the URL: http://eprints.imtlucca.it/id/eprint/1120
2012-02-14T14:31:41Z
Assortative model for social networks
In this Brief Report we present a version of a network growth model, generalized in order to describe the behavior of social networks. The case of study considered is the preprint archive at cul.arxiv.org. Each node corresponds to a scientist, and a link is present whenever two authors wrote a paper together. This graph is a nice example of degree-assortative network, that is, to say a network where sites with similar degree are connected to each other. The model presented is one of the few able to reproduce such behavior, giving some insight on the microscopic dynamics at the basis of the graph structure.
Michele Catanzaro
Guido Caldarelli
guido.caldarelli@imtlucca.it
Luciano Pietronero
2012-02-14T14:21:09Z
2013-11-20T14:58:49Z
http://eprints.imtlucca.it/id/eprint/1119
This item is in the repository with the URL: http://eprints.imtlucca.it/id/eprint/1119
2012-02-14T14:21:09Z
Vertex intrinsic fitness: How to produce arbitrary scale-free networks
We study a recent model of random networks based on the presence of an intrinsic character of the vertices called fitness. The vertex fitnesses are drawn from a given probability distribution density. The edges between pairs of vertices are drawn according to a linking probability function depending on the fitnesses of the two vertices involved. We study here different choices for the probability distribution densities and the linking functions. We find that, irrespective of the particular choices, the generation of scale-free networks is straightforward. We then derive the general conditions under which scale-free behavior appears. This model could then represent a possible explanation for the ubiquity and robustness of such structures.
Vito D. P. Servedio
Guido Caldarelli
guido.caldarelli@imtlucca.it
Paolo Buttà
2012-02-14T13:52:35Z
2018-03-08T17:08:11Z
http://eprints.imtlucca.it/id/eprint/1118
This item is in the repository with the URL: http://eprints.imtlucca.it/id/eprint/1118
2012-02-14T13:52:35Z
Emergence of complexity in financial networks
We present here a brief summary of the various possible applications of network theory in the field of finance. Since we want to characterize different systems by means of simple and universal features, graph theory could represent a rather powerful methodology. In the following we report our activity in three different subfields, namely the board and director networks, the networks formed by prices correlations and the stock ownership networks. In most of the cases these three kind of networks display scale-free properties making them interesting in their own. Nevertheless, we want to stress here that the main utility of this methodology is to provide new measures of the real data sets in order to validate the different models.
Guido Caldarelli
guido.caldarelli@imtlucca.it
Stefano Battiston
Diego Garlaschelli
diego.garlaschelli@imtlucca.it
Michele Catanzaro
2012-02-14T13:25:27Z
2012-02-14T13:25:27Z
http://eprints.imtlucca.it/id/eprint/1117
This item is in the repository with the URL: http://eprints.imtlucca.it/id/eprint/1117
2012-02-14T13:25:27Z
The corporate boards networks
In this work we apply network theory to detect in a quantitative fashion some of the characters of the system composed by companies and their boards of directors. Modelling this as a bipartite graph, we can derive two networks (one for the companies and one for the directors) and apply to them the standard graph analysis instruments. The emerging picture shows an environment where the exchange of information and mutual influences, conveyed by interlocks between boards, is predominant. Such a result should be taken into account when modelling this system.
Guido Caldarelli
guido.caldarelli@imtlucca.it
Michele Catanzaro
2012-02-14T13:19:55Z
2012-02-14T13:19:55Z
http://eprints.imtlucca.it/id/eprint/1116
This item is in the repository with the URL: http://eprints.imtlucca.it/id/eprint/1116
2012-02-14T13:19:55Z
Social network growth with assortative mixing
Networks representing social systems display specific features that put them apart from biological and technological ones. In particular, the number of links attached to a node is positively correlated to that of its nearest neighbours. We develop a model that reproduces this feature, starting from microscopical mechanisms of growth. The statistical properties arising from the simulations are in good agreement with those of the real-world social networks of scientists co-authoring papers in condensed matter physics. Moreover, the model highlights the determinant role of correlations in shaping the network's topology.
Michele Catanzaro
Guido Caldarelli
guido.caldarelli@imtlucca.it
Luciano Pietronero
2012-02-13T14:54:52Z
2018-03-08T17:07:48Z
http://eprints.imtlucca.it/id/eprint/1115
This item is in the repository with the URL: http://eprints.imtlucca.it/id/eprint/1115
2012-02-13T14:54:52Z
The scale-free topology of market investments
We propose a network description of large market investments, where both stocks and shareholders are represented as vertices connected by weighted links corresponding to shareholdings. In this framework, the in-degree (kin) and the sum of incoming link weights (v) of an investor correspond to the number of assets held (portfolio diversification) and to the invested wealth (portfolio volume), respectively. An empirical analysis of three different real markets reveals that the distributions of both kin and v display power-law tails with exponents γ and α. Moreover, we find that kinscales as a power-law function of v with an exponent β. Remarkably, despite the values of α, β and γ differ across the three markets, they are always governed by the scaling relation β=(1-α)/(1-γ). We show that these empirical findings can be reproduced by a recent model relating the emergence of scale-free networks to an underlying Paretian distribution of ‘hidden’ vertex properties.
Diego Garlaschelli
diego.garlaschelli@imtlucca.it
Stefano Battiston
Maurizio Castri
Vito D. P. Servedio
Guido Caldarelli
guido.caldarelli@imtlucca.it
2012-02-13T14:30:32Z
2013-11-21T09:04:26Z
http://eprints.imtlucca.it/id/eprint/1114
This item is in the repository with the URL: http://eprints.imtlucca.it/id/eprint/1114
2012-02-13T14:30:32Z
Detecting communities in large networks
We develop an algorithm to detect community structure in complex networks. The algorithm is based on spectral methods and takes into account weights and link orientation. Since the method detects efficiently clustered nodes in large networks even when these are not sharply partitioned, it turns to be specially suitable for the analysis of social and information networks. We test the algorithm on a large-scale data-set from a psychological experiment of word association. In this case, it proves to be successful both in clustering words, and in uncovering mental association patterns.
Andrea Capocci
Vito D. P. Servedio
Guido Caldarelli
guido.caldarelli@imtlucca.it
Francesca Colaiori
2012-02-13T14:15:03Z
2012-02-13T14:15:03Z
http://eprints.imtlucca.it/id/eprint/1113
This item is in the repository with the URL: http://eprints.imtlucca.it/id/eprint/1113
2012-02-13T14:15:03Z
Communities Detection in Large Networks
We develop an algorithm to detect community structure in complex networks. The algorithm is based on spectral methods and takes into account weights and links orientations. Since the method detects efficiently clustered nodes in large networks even when these are not sharply partitioned, it turns to be specially suitable to the analysis of social and information networks. We test the algorithm on a large-scale data-set from a psychological experiment of word association. In this case, it proves to be successful both in clustering words, and in uncovering mental association patterns.
Andrea Capocci
Vito D. P. Servedio
Guido Caldarelli
guido.caldarelli@imtlucca.it
Francesca Colaiori
2012-02-13T13:48:45Z
2018-03-08T17:07:31Z
http://eprints.imtlucca.it/id/eprint/1112
This item is in the repository with the URL: http://eprints.imtlucca.it/id/eprint/1112
2012-02-13T13:48:45Z
Food-web topology: universal scaling in food-web structure? (reply)
Although Camacho and Arenas raise potentially interesting points, we believe that some of their arguments are flawed or undermined by poor statistics, and therefore that they do not invalidate our result.
Diego Garlaschelli
diego.garlaschelli@imtlucca.it
Guido Caldarelli
guido.caldarelli@imtlucca.it
Luciano Pietronero
2012-02-03T15:01:41Z
2013-11-21T09:06:06Z
http://eprints.imtlucca.it/id/eprint/1111
This item is in the repository with the URL: http://eprints.imtlucca.it/id/eprint/1111
2012-02-03T15:01:41Z
Loops structure of the Internet at the autonomous system level
We present here a study of the clustering and loops in a graph of the Internet at the autonomous systems level. We show that, even if the whole structure is changing with time, the statistical distributions of loops of order 3, 4, and 5 remain stable during the evolution. Moreover, we will bring evidence that the Internet graphs show characteristic Markovian signatures, since the structure is very well described by two-point correlations between the degrees of the vertices. This indeed proves that the Internet belongs to a class of network in which the two-point correlation is sufficient to describe their whole local (and thus global) structure. Data are also compared to present Internet models.
Ginestra Bianconi
Guido Caldarelli
guido.caldarelli@imtlucca.it
Andrea Capocci
2012-02-03T14:52:07Z
2018-03-08T17:07:59Z
http://eprints.imtlucca.it/id/eprint/1110
This item is in the repository with the URL: http://eprints.imtlucca.it/id/eprint/1110
2012-02-03T14:52:07Z
The topology of shareholding networks
We study the statistical properties of the network of shareholding relationships in the Italian stock market (MIB) and in two US stock markets (NYSE and NASDAQ). The networks are found to be scale free a feature which doesn't seem to be in accord with classical theories of portfolio optimization. Several statistical properties differ across markets and allow for a classification. We introduce two quantities, HI and SI, analogous to in-degree and out-degree for weighted graphs. The distribution of HI and SI allow us to characterize from a statistical perspective the individual ownership concentration of stocks and the individual power of holders. They also suggest two different global pictures of the structure of the networks: the MIB seems characterized by medium size holders controlling separate subsets of stocks, while the US markets seem characterized by very large holders sharing control over subsets of stocks.
Stefano Battiston
Diego Garlaschelli
diego.garlaschelli@imtlucca.it
Guido Caldarelli
guido.caldarelli@imtlucca.it
2012-02-03T14:29:51Z
2014-12-18T16:02:51Z
http://eprints.imtlucca.it/id/eprint/1109
This item is in the repository with the URL: http://eprints.imtlucca.it/id/eprint/1109
2012-02-03T14:29:51Z
Preferential attachment in the growth of social networks: the internet encyclopedia Wikipedia
We present an analysis of the statistical properties and growth of the free on-line encyclopedia Wikipedia. By describing topics by vertices and hyperlinks between them as edges, we can represent this encyclopedia as a directed graph. The topological properties of this graph are in close analogy with those of the World Wide Web, despite the very different growth mechanism. In particular, we measure a scale-invariant distribution of the in and out degree and we are able to reproduce these features by means of a simple statistical model. As a major consequence, Wikipedia growth can be described by local rules such as the preferential attachment mechanism, though users, who are responsible of its evolution, can act globally on the network.
Andrea Capocci
Vito D. P. Servedio
Francesca Colaiori
Luciana Buriol
Debora Donato
Stefano Leonardi
Guido Caldarelli
guido.caldarelli@imtlucca.it
2012-02-03T13:56:18Z
2018-03-08T17:07:02Z
http://eprints.imtlucca.it/id/eprint/1108
This item is in the repository with the URL: http://eprints.imtlucca.it/id/eprint/1108
2012-02-03T13:56:18Z
Graph Theory and Food Webs
Recently the study of complex networks has received great attention. One of the most interesting applications of these concepts is found in the study of food webs. Food webs provide fascinating examples of biological organization in ecological communities and display characteristic and unexpected statistical properties. In particular, comparison to other complex networks shows that food webs lack the scale-free properties observed in almost all other artificial and natural networks. That is, the frequency distribution for the degree (numer of different predators per species) does not display scale-free behavior. Nevertheless, we show here that self-similiar and universal behavior are still present. By considering food webs as transportation networks (for the flow of resources between species), we can recover scaling properties typical of other transportation system, such as vascular and river networks. The importance of these properties for models of structure in food webs is discussed.
Cécile Caretta Cartozo
Diego Garlaschelli
diego.garlaschelli@imtlucca.it
Guido Caldarelli
guido.caldarelli@imtlucca.it
2012-02-01T16:12:55Z
2014-12-18T15:56:24Z
http://eprints.imtlucca.it/id/eprint/1107
This item is in the repository with the URL: http://eprints.imtlucca.it/id/eprint/1107
2012-02-01T16:12:55Z
Fitness model for the Italian interbank money market
We use the theory of complex networks in order to quantitatively characterize the formation of communities in a particular financial market. The system is composed by different banks exchanging on a daily basis loans and debts of liquidity. Through topological analysis and by means of a model of network growth we can determine the formation of different group of banks characterized by different business strategy. The model based on Pareto’s law makes no use of growth or preferential attachment and it reproduces correctly all the various statistical properties of the system. We believe that this network modeling of the market could be an efficient way to evaluate the impact of different policies in the market of liquidity.
Giulia De Masi
Giulia Iori
Guido Caldarelli
guido.caldarelli@imtlucca.it
2012-02-01T16:07:06Z
2018-03-08T17:07:17Z
http://eprints.imtlucca.it/id/eprint/1106
This item is in the repository with the URL: http://eprints.imtlucca.it/id/eprint/1106
2012-02-01T16:07:06Z
Temperature in complex networks
Various statistical-mechanics approaches to complex networks have been proposed to describe expected topological properties in terms of ensemble averages. Here we extend this formalism by introducing the fundamental concept of graph temperature, controlling the degree of topological optimization of a network. We recover the temperature-dependent version of various important models as particular cases of our approach, and show examples where, remarkably, the onset of a percolation transition, a scale-free degree distribution, correlations and clustering can be understood as natural properties of an optimized (low-temperature) topology. We then apply our formalism to real weighted networks and we compute their temperature, finding that various techniques used to extract information from complex networks are again particular cases of our approach.
Diego Garlaschelli
diego.garlaschelli@imtlucca.it
Sebastian E. Ahnert
Thomas M.A. Fink
Guido Caldarelli
guido.caldarelli@imtlucca.it
2012-02-01T15:59:45Z
2013-11-21T09:19:40Z
http://eprints.imtlucca.it/id/eprint/1105
This item is in the repository with the URL: http://eprints.imtlucca.it/id/eprint/1105
2012-02-01T15:59:45Z
Trading strategies in the Italian interbank market
Using a data set which includes all transactions among banks in the Italian money market, we study their trading strategies and the dependence among them. We use the Fourier method to compute the variance–covariance matrix of trading strategies. Our results indicate that well defined patterns arise. Two main communities of banks, which can be coarsely identified as small and large banks, emerge.
Giulia Iori
Renato Renò
Giulia De Masi
Guido Caldarelli
guido.caldarelli@imtlucca.it
2012-02-01T15:39:59Z
2018-03-08T17:09:14Z
http://eprints.imtlucca.it/id/eprint/1104
This item is in the repository with the URL: http://eprints.imtlucca.it/id/eprint/1104
2012-02-01T15:39:59Z
Ensemble approach to the analysis of weighted networks
We present an approach to the analysis of weighted networks, by providing a straightforward generalization of any network measure defined on unweighted networks, such as the average degree of the nearest neighbors, the clustering coefficient, the “betweenness,” the distance between two nodes, and the diameter of a network. All these measures are well established for unweighted networks but have hitherto proven difficult to define for weighted networks. Our approach is based on the translation of a weighted network into an ensemble of edges. Further introducing this approach we demonstrate its advantages by applying the clustering coefficient constructed in this way to two real-world weighted networks.
Sebastian E. Ahnert
Diego Garlaschelli
diego.garlaschelli@imtlucca.it
Thomas M.A. Fink
Guido Caldarelli
guido.caldarelli@imtlucca.it
2012-02-01T15:35:22Z
2018-03-08T17:09:24Z
http://eprints.imtlucca.it/id/eprint/1103
This item is in the repository with the URL: http://eprints.imtlucca.it/id/eprint/1103
2012-02-01T15:35:22Z
Interplay between topology and dynamics in the World Trade Web
We present an empirical analysis of the network formed by the trade relationships between all world countries, or World Trade Web (WTW). Each (directed) link is weighted by the amount of wealth flowing between two countries, and each country is characterized by the value of its Gross Domestic Product (GDP). By analysing a set of year-by-year data covering the time interval 1950–2000, we show that the dynamics of all GDP values and the evolution of the WTW (trade flow and topology) are tightly coupled. The probability that two countries are connected depends on their GDP values, supporting recent theoretical models relating network topology to the presence of a `hidden' variable (or fitness). On the other hand, the topology is shown to determine the GDP values due to the exchange between countries. This leads us to a new framework where the fitness value is a dynamical variable determining, and at the same time depending on, network topology in a continuous feedback.
Diego Garlaschelli
diego.garlaschelli@imtlucca.it
Tiziana Di Matteo
Tomaso Aste
Guido Caldarelli
guido.caldarelli@imtlucca.it
Maria Immacolata Loffredo
2012-02-01T14:07:02Z
2014-12-18T15:51:42Z
http://eprints.imtlucca.it/id/eprint/1102
This item is in the repository with the URL: http://eprints.imtlucca.it/id/eprint/1102
2012-02-01T14:07:02Z
Uncovering the topology of configuration space networks
The configuration space network (CSN) of a dynamical system is an effective approach to represent the ensemble of configurations sampled during a simulation and their dynamic connectivity. To elucidate the connection between the CSN topology and the underlying free-energy landscape governing the system dynamics and thermodynamics, an analytical solution is provided to explain the heavy tail of the degree distribution, neighbor connectivity, and clustering coefficient. This derivation allows us to understand the universal CSN topology observed in systems ranging from a simple quadratic well to the native state of the beta3s peptide and a two-dimensional lattice heteropolymer. Moreover, CSNs are shown to fall in the general class of complex networks described by the fitness model.
David Gfeller
David Morton de Lachapelle
Paolo De Los Rios
Guido Caldarelli
guido.caldarelli@imtlucca.it
Francesco Rao
2012-02-01T14:01:47Z
2018-03-08T17:09:03Z
http://eprints.imtlucca.it/id/eprint/1101
This item is in the repository with the URL: http://eprints.imtlucca.it/id/eprint/1101
2012-02-01T14:01:47Z
Self-organized network evolution coupled to extremal dynamics
The interplay between topology and dynamics in complex networks is a fundamental but widely unexplored problem. Here, we study this phenomenon on a prototype model in which the network is shaped by a dynamical variable. We couple the dynamics of the Bak–Sneppen evolution model with the rules of the so-called fitness network model for establishing the topology of a network; each vertex is assigned a 'fitness', and the vertex with minimum fitness and its neighbours are updated in each iteration. At the same time, the links between the updated vertices and all other vertices are drawn anew with a fitness-dependent connection probability. We show analytically and numerically that the system self-organizes to a non-trivial state that differs from what is obtained when the two processes are decoupled. A power-law decay of dynamical and topological quantities above a threshold emerges spontaneously, as well as a feedback between different dynamical regimes and the underlying correlation and percolation properties of the network.
Diego Garlaschelli
diego.garlaschelli@imtlucca.it
Andrea Capocci
Guido Caldarelli
guido.caldarelli@imtlucca.it
2012-02-01T13:51:08Z
2012-02-01T13:51:48Z
http://eprints.imtlucca.it/id/eprint/1100
This item is in the repository with the URL: http://eprints.imtlucca.it/id/eprint/1100
2012-02-01T13:51:08Z
The Italian interbank network: statistical properties and a simple model
We use the theory of complex networks in order to quantitatively characterize the structure of reciprocal expositions of Italian banks in the interbank money market market. We observe two main different strategies of banks: small banks tend to be the lender of the system, while large banks are borrowers. We propose a model to reproduce the main statistical features of this market. Moreover the network analysis allows us to investigate properties of robustness of this system.
Giulia De Masi
Giulia Iori
Guido Caldarelli
guido.caldarelli@imtlucca.it
2012-02-01T13:17:52Z
2013-11-21T09:07:26Z
http://eprints.imtlucca.it/id/eprint/1099
This item is in the repository with the URL: http://eprints.imtlucca.it/id/eprint/1099
2012-02-01T13:17:52Z
Spectral methods cluster words of the same class in a syntactic dependency network
We analyze here a particular kind of linguistic network where vertices represent words and edges stand for syntactic relationships between words. The statistical properties of these networks have been recently studied and various features such as the small-world phenomenon and a scale-free distribution of degrees have been found. Our work focuses on four classes of words: verbs, nouns, adverbs and adjectives. Here, we use spectral methods sorting vertices. We show that the ordering clusters words of the same class. For nouns and verbs, the cluster size distribution clearly follows a power-law distribution that cannot be explained by a null hypothesis. Long-range correlations are found between vertices in the ordering provided by the spectral method. The findings support the use of spectral methods for detecting community structure.
Ramon Ferrer I Cancho
Andrea Capocci
Guido Caldarelli
guido.caldarelli@imtlucca.it
2012-02-01T12:00:55Z
2016-04-06T08:58:18Z
http://eprints.imtlucca.it/id/eprint/1098
This item is in the repository with the URL: http://eprints.imtlucca.it/id/eprint/1098
2012-02-01T12:00:55Z
A network analysis of the Italian overnight money market
The objective of this paper is to analyse the network topology of the Italian segment of the European overnight money market through methods of statistical mechanics applied to complex networks. We investigate differences in the activities of banks of different sizes and the evolution of their connectivity structure over the maintenance period. The main purpose of the analysis is to establish the potential implications of the current institutional arrangements on the stability of the banking system and to assess the efficiency of the interbank market in terms of absence of speculative and preferential trading relationships.
Giulia Iori
Giulia De Masi
Ovidiu Vasile Precup
Giampaolo Gabbi
Guido Caldarelli
guido.caldarelli@imtlucca.it
2012-02-01T11:47:12Z
2012-02-01T11:47:52Z
http://eprints.imtlucca.it/id/eprint/1097
This item is in the repository with the URL: http://eprints.imtlucca.it/id/eprint/1097
2012-02-01T11:47:12Z
Taxonomy and clustering in collaborative systems: the case of the on-line encyclopedia Wikipedia
In this paper we investigate the nature and structure of the relation between imposed classifications and real clustering in a particular case of a scale-free network given by the on-line encyclopedia Wikipedia. We find a statistical similarity in the distributions of community sizes both by using the top-down approach of the categories division present in the archive and in the bottom-up procedure of community detection given by an algorithm based on the spectral properties of the graph. Regardless of the statistically similar behaviour, the two methods provide a rather different division of the articles, thereby signaling that the nature and presence of power laws is a general feature for these systems and cannot be used as a benchmark to evaluate the suitability of a clustering method.
Andrea Capocci
Francesco Rao
Guido Caldarelli
guido.caldarelli@imtlucca.it
2012-02-01T11:43:36Z
2013-11-21T09:43:01Z
http://eprints.imtlucca.it/id/eprint/1096
This item is in the repository with the URL: http://eprints.imtlucca.it/id/eprint/1096
2012-02-01T11:43:36Z
Folksonomies and clustering in the collaborative system CiteULike
We analyze CiteULike, an online collaborative tagging system where users bookmark and annotate scientific papers. Such a system can be naturally represented as a tri-partite graph whose nodes represent papers, users and tags connected by individual tag assignments. The semantics of tags is studied here, in order to uncover the hidden relationships between tags. We find that the clustering coefficient can be used to analyze the semantical patterns among tags.
Andrea Capocci
Guido Caldarelli
guido.caldarelli@imtlucca.it
2012-02-01T11:39:20Z
2018-03-08T17:06:00Z
http://eprints.imtlucca.it/id/eprint/1095
This item is in the repository with the URL: http://eprints.imtlucca.it/id/eprint/1095
2012-02-01T11:39:20Z
Quantifying the taxonomic diversity in real species communities
We analyze several florae (collections of plant species populating specific areas) in different geographic and climatic regions. For every list of species we produce a taxonomic classification tree and we consider its statistical properties. We find that regardless of the geographical location, the climate and the environment all species collections have universal statistical properties that we show to be also robust in time. We then compare observed data sets with simulated communities obtained by randomly sampling a large pool of species from all over the world. We find differences in the behavior of the statistical properties of the corresponding taxonomic trees. Our results suggest that it is possible to distinguish quantitatively real species assemblages from random collections and thus demonstrate the existence of correlations between species.
Cécile Caretta Cartozo
Diego Garlaschelli
diego.garlaschelli@imtlucca.it
Carlo Ricotta
Marc Barthélemy
Guido Caldarelli
guido.caldarelli@imtlucca.it
2012-02-01T11:33:12Z
2018-03-08T17:05:45Z
http://eprints.imtlucca.it/id/eprint/1094
This item is in the repository with the URL: http://eprints.imtlucca.it/id/eprint/1094
2012-02-01T11:33:12Z
Applying weighted network measures to microarray distance matrices
In recent work we presented a new approach to the analysis of weighted networks, by providing a straightforward generalization of any network measure defined on unweighted networks. This approach is based on the translation of a weighted network into an ensemble of edges, and is particularly suited to the analysis of fully connected weighted networks. Here we apply our method to several such networks including distance matrices, and show that the clustering coefficient, constructed by using the ensemble approach, provides meaningful insights into the systems studied. In the particular case of two datasets from microarray experiments the clustering coefficient identifies a number of biologically significant genes, outperforming existing identification approaches.
Sebastian E. Ahnert
Diego Garlaschelli
diego.garlaschelli@imtlucca.it
Thomas M.A. Fink
Guido Caldarelli
guido.caldarelli@imtlucca.it
2012-02-01T11:21:00Z
2013-11-06T10:33:36Z
http://eprints.imtlucca.it/id/eprint/1093
This item is in the repository with the URL: http://eprints.imtlucca.it/id/eprint/1093
2012-02-01T11:21:00Z
Complex Networks: from Biology to Information Technology - Preface
Alain Barrat
Stefano Boccaletti
Guido Caldarelli
guido.caldarelli@imtlucca.it
Alessandro Chessa
alessandro.chessa@imtlucca.it
Vito Latora
Adilson E. Motter
2012-02-01T11:07:59Z
2018-03-08T17:06:15Z
http://eprints.imtlucca.it/id/eprint/1092
This item is in the repository with the URL: http://eprints.imtlucca.it/id/eprint/1092
2012-02-01T11:07:59Z
A self-organized model for network evolution
Here we provide a detailed analysis, along with some extensions and additonal investigations, of a recently proposed [1] self-organized model for the evolution of complex networks. Vertices of the network are characterized by a fitness variable evolving through an extremal dynamics process, as in the Bak-Sneppen [2] model representing a prototype of Self-Organized Criticality. The network topology is in turn shaped by the fitness variable itself, as in the fitness network model [3]. The system self-organizes to a nontrivial state, characterized by a power-law decay of dynamical and topological quantities above a critical threshold. The interplay between topology and dynamics in the system is the key ingredient leading to an unexpected behaviour of these quantities.
Guido Caldarelli
guido.caldarelli@imtlucca.it
Andrea Capocci
Diego Garlaschelli
diego.garlaschelli@imtlucca.it
2012-02-01T10:59:01Z
2018-03-08T17:05:00Z
http://eprints.imtlucca.it/id/eprint/1091
This item is in the repository with the URL: http://eprints.imtlucca.it/id/eprint/1091
2012-02-01T10:59:01Z
On the rich-club effect in dense and weighted networks
For many complex networks present in nature only a single instance, usually of large size, is available. Any measurement made on this single instance cannot be repeated on different realizations. In order to detect significant patterns in a real-world network it is therefore crucial to compare the measured results with a null model counterpart. Here we focus on dense and weighted networks, proposing a suitable null model and studying the behaviour of the degree correlations as measured by the rich-club coefficient. Our method solves an existing problem with the randomization of dense unweighted graphs, and at the same time represents a generalization of the rich-club coefficient to weighted networks which is complementary to other recently proposed ones.
Vinko Zlatic
Ginestra Bianconi
Albert Díaz-Guilera
Diego Garlaschelli
diego.garlaschelli@imtlucca.it
Francesco Rao
Guido Caldarelli
guido.caldarelli@imtlucca.it
2012-01-26T14:23:51Z
2014-12-18T15:38:41Z
http://eprints.imtlucca.it/id/eprint/1087
This item is in the repository with the URL: http://eprints.imtlucca.it/id/eprint/1087
2012-01-26T14:23:51Z
Invasion percolation on a tree and queueing models
We study the properties of the Barabási model of queuing [ A.-L. Barabási Nature (London) 435 207 (2005); J. G. Oliveira and A.-L. Barabási Nature (London) 437 1251 (2005)] in the hypothesis that the number of tasks grows with time steadily. Our analytical approach is based on two ingredients. First we map exactly this model into an invasion percolation dynamics on a Cayley tree. Second we use the theory of biased random walks. In this way we obtain the following results: the stationary-state dynamics is a sequence of causally and geometrically connected bursts of execution activities with scale-invariant size distribution. We recover the correct waiting-time distribution PW(τ)∼τ−3/2 at the stationary state (as observed in different realistic data). Finally we describe quantitatively the dynamics out of the stationary state quantifying the power-law slow approach to stationarity both in single dynamical realization and in average. These results can be generalized to the case of a stochastic increase in the queue length in time with limited fluctuations. As a limit case we recover the situation in which the queue length fluctuates around a constant average value.
Andrea Gabrielli
Guido Caldarelli
guido.caldarelli@imtlucca.it
2012-01-26T14:19:40Z
2014-12-05T09:24:53Z
http://eprints.imtlucca.it/id/eprint/1086
This item is in the repository with the URL: http://eprints.imtlucca.it/id/eprint/1086
2012-01-26T14:19:40Z
Invasion percolation and critical transient in the Barabási Model of human dynamics
We introduce an exact probabilistic description for L=2 of the Barabási model for the dynamics of a list of L tasks. This permits us to study the problem out of the stationary state and to solve explicitly the extremal limit case where a critical behavior for the waiting time distribution is observed. This behavior deviates at any finite time from that of the stationary state. We study also the characteristic relaxation time for finite time deviations from stationarity in all cases showing that it diverges in the extremal limit, confirming that these deviations are important at all time.
Andrea Gabrielli
Guido Caldarelli
guido.caldarelli@imtlucca.it
2012-01-26T14:09:16Z
2014-12-18T15:37:28Z
http://eprints.imtlucca.it/id/eprint/1085
This item is in the repository with the URL: http://eprints.imtlucca.it/id/eprint/1085
2012-01-26T14:09:16Z
Random hypergraphs and their applications
In the last few years we have witnessed the emergence, primarily in online communities, of new types of social networks that require for their representation more complex graph structures than have been employed in the past. One example is the folksonomy, a tripartite structure of users, resources, and tags—labels collaboratively applied by the users to the resources in order to impart meaningful structure on an otherwise undifferentiated database. Here we propose a mathematical model of such tripartite structures that represents them as random hypergraphs. We show that it is possible to calculate many properties of this model exactly in the limit of large network size and we compare the results against observations of a real folksonomy, that of the online photography website Flickr. We show that in some cases the model matches the properties of the observed network well, while in others there are significant differences, which we find to be attributable to the practice of multiple tagging, i.e., the application by a single user of many tags to one resource or one tag to many resources
Gourab Ghoshal
Vinko Zlatic
Guido Caldarelli
guido.caldarelli@imtlucca.it
M.E.J. Newman
2012-01-26T13:53:54Z
2014-12-18T15:35:35Z
http://eprints.imtlucca.it/id/eprint/1084
This item is in the repository with the URL: http://eprints.imtlucca.it/id/eprint/1084
2012-01-26T13:53:54Z
Hypergraph topological quantities for tagged social networks
Recent years have witnessed the emergence of a new class of social networks, which require us to move beyond previously employed representations of complex graph structures. A notable example is that of the folksonomy, an online process where users collaboratively employ tags to resources to impart structure to an otherwise undifferentiated database. In a recent paper, we proposed a mathematical model that represents these structures as tripartite hypergraphs and defined basic topological quantities of interest. In this paper, we extend our model by defining additional quantities such as edge distributions, vertex similarity and correlations as well as clustering. We then empirically measure these quantities on two real life folksonomies, the popular online photo sharing site Flickr and the bookmarking site CiteULike. We find that these systems share similar qualitative features with the majority of complex networks that have been previously studied. We propose that the quantities and methodology described here can be used as a standard tool in measuring the structure of tagged networks.
Vinko Zlatic
Gourab Ghoshal
Guido Caldarelli
guido.caldarelli@imtlucca.it
2012-01-26T10:49:27Z
2013-11-20T15:59:36Z
http://eprints.imtlucca.it/id/eprint/1083
This item is in the repository with the URL: http://eprints.imtlucca.it/id/eprint/1083
2012-01-26T10:49:27Z
PageRank equation and localization in the WWW
We show that the PageRank in a network can be represented as the solution of a differential equation discretized over a directed graph. By exploiting a formal relationship with the time-independent Schrödinger equation it is possible to interpret hub formation and related phenomena as a wave-like localization process in the presence of disorder and trapping potentials. The result opens new perspectives in the physics of networks with interdisciplinary connections and opens the way to the employment of various mathematical techniques to the analysis of self-organization in structured systems. Applications are envisaged in the World-Wide Web, traffic, social and biological networks.
Nicola Perra
Vinko Zlatic
Alessandro Chessa
alessandro.chessa@imtlucca.it
Claudio Conti
Debora Donato
Guido Caldarelli
guido.caldarelli@imtlucca.it
2012-01-26T10:23:28Z
2012-01-26T10:23:28Z
http://eprints.imtlucca.it/id/eprint/1082
This item is in the repository with the URL: http://eprints.imtlucca.it/id/eprint/1082
2012-01-26T10:23:28Z
A Networked World
Just over a decade ago, in June 1998, a curious three-page paper appeared in Nature. In it, the authors - two applied mathematicians - reported a link between the structure of the US electrical grid and the wiring of a nematode worm's neural system. They also noted that these patterns were strikingly similar in their structure to the social networks of Hollywood actors, one of the few such networks for which the authors could find extensive data. It is hard to imagine a more bizarre melding of topics in one study.
Mark Buchanan
Guido Caldarelli
guido.caldarelli@imtlucca.it
2012-01-26T10:01:25Z
2012-01-26T10:55:18Z
http://eprints.imtlucca.it/id/eprint/1081
This item is in the repository with the URL: http://eprints.imtlucca.it/id/eprint/1081
2012-01-26T10:01:25Z
A PageRank-based preferential attachment model for the evolution of the World Wide Web
We propose a model of network growth aimed at mimicking the evolution of the World Wide Web. To this purpose, we take as a key quantity, in the network evolution, the centrality or importance of a vertex as measured by its PageRank. Using a preferential attachment rule and a rewiring procedure based on this quantity, we can reproduce most of the topological properties of the system.
P. Giammatteo
Debora Donato
Vinko Zlatic
Guido Caldarelli
guido.caldarelli@imtlucca.it
2012-01-26T09:16:41Z
2016-04-07T08:03:08Z
http://eprints.imtlucca.it/id/eprint/1080
This item is in the repository with the URL: http://eprints.imtlucca.it/id/eprint/1080
2012-01-26T09:16:41Z
Topologically biased random walk and community finding in networks
We present an approach of topology biased random walks for undirected networks. We focus on a one-parameter family of biases, and by using a formal analogy with perturbation theory in quantum mechanics we investigate the features of biased random walks. This analogy is extended through the use of parametric equations of motion to study the features of random walks vs parameter values. Furthermore, we show an analysis of the spectral gap maximum associated with the value of the second eigenvalue of the transition matrix related to the relaxation rate to the stationary state. Applications of these studies allow ad hoc algorithms for the exploration of complex networks and their communities.
Vinko Zlatic
Andrea Gabrielli
Guido Caldarelli
guido.caldarelli@imtlucca.it
2012-01-26T09:06:19Z
2013-11-21T11:14:11Z
http://eprints.imtlucca.it/id/eprint/1079
This item is in the repository with the URL: http://eprints.imtlucca.it/id/eprint/1079
2012-01-26T09:06:19Z
Population Dynamics On Complex Food Webs
In this work we analyze the topological and dynamical properties of a simple model of complex food webs, namely the niche model. In order to underline competition among species, we introduce "prey" and "predators" weighted overlap graphs derived from the niche model and compare synthetic food webs with real data. Doing so, we find new tests for the goodness of synthetic food web models and indicate a possible direction of improvement for existing ones. We then exploit the weighted overlap graphs to define a competition kernel for Lotka–Volterra population dynamics and find that for such a model the stability of food webs decreases with its ecological complexity.
Gian Marco Palamara
Vinko Zlatic
Antonio Scala
Guido Caldarelli
guido.caldarelli@imtlucca.it
2012-01-25T13:47:35Z
2012-01-25T13:47:35Z
http://eprints.imtlucca.it/id/eprint/1078
This item is in the repository with the URL: http://eprints.imtlucca.it/id/eprint/1078
2012-01-25T13:47:35Z
Invasion percolation and the time scaling behavior of a queuing model of human dynamics
In this paper we study the properties of the Barabási model of queuing under the hypothesis that the number of tasks is steadily growing in time. We map this model exactly onto an invasion percolation dynamics on a Cayley tree. This allows us to recover the correct waiting time distribution PW(τ)~τ−3/2 at the stationary state (as observed in different realistic data) and also to characterize it as a sequence of causally and geometrically connected bursts of activity. We also find that the approach to stationarity is very slow.
Andrea Gabrielli
Guido Caldarelli
guido.caldarelli@imtlucca.it
2012-01-25T13:12:31Z
2012-01-25T13:12:31Z
http://eprints.imtlucca.it/id/eprint/1077
This item is in the repository with the URL: http://eprints.imtlucca.it/id/eprint/1077
2012-01-25T13:12:31Z
Scale-free networks : complex webs in nature and technology
A variety of different social, natural and technological systems can be described by the same mathematical framework. This holds from the Internet to food webs and to boards of company directors. In all these situations, a graph of the elements of the system and their interconnections displays a universal feature. There are only a few elements with many connections and many elements with few connections. This book reports the experimental evidence of these ‘Scale-free networks’ and provides students and researchers with a corpus of theoretical results and algorithms to analyse and understand these features. The content of this book and the exposition makes it a clear textbook for beginners and a reference book for experts.
Guido Caldarelli
guido.caldarelli@imtlucca.it
2012-01-20T10:45:29Z
2012-01-25T13:10:14Z
http://eprints.imtlucca.it/id/eprint/1076
This item is in the repository with the URL: http://eprints.imtlucca.it/id/eprint/1076
2012-01-20T10:45:29Z
(edited by) Large scale structure and dynamics of complex networks: from information technology to finance and natural science
This book is the culmination of three years of research effort on a multidisciplinary project in which physicists, mathematicians, computer scientists and social scientists worked together to arrive at a unifying picture of complex networks. The contributed chapters form a reference for the various problems in data analysis visualization and modeling of complex networks.
Guido Caldarelli
guido.caldarelli@imtlucca.it
Alessandro Vespignani