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Quantifying randomness in real networks

Orsini, Chiara and Dankulov, Marija M. and Colomer-de-Simón, Pol and Jamakovic, Almerima and Mahadevan, Priya and Vahdat, Amin and Bassler, Kevin E. and Toroczkai, Zoltán and Boguñá, Marián and Caldarelli, Guido and Fortunato, Santo and Krioukov, Dmitri Quantifying randomness in real networks. Nature Communications, 6 (8627). ISSN 2041-1723 (2015)

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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.

Item Type: Article
Identification Number: 10.1038/ncomms9627
Subjects: H Social Sciences > H Social Sciences (General)
Q Science > QA Mathematics
Research Area: Economics and Institutional Change
Depositing User: Caterina Tangheroni
Date Deposited: 02 Nov 2015 14:20
Last Modified: 02 Nov 2015 14:20
URI: http://eprints.imtlucca.it/id/eprint/2801

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