Logo eprints

Modeling networks with a growing feature-structure

Crimaldi, Irene and Del Vicario, Michela and Morrison, Greg and Quattrociocchi, Walter and Riccaboni, Massimo Modeling networks with a growing feature-structure. Interdisciplinary Information Sciences. ISSN 1340-9050 (In Press) (2017)

Full text not available from this repository.

Abstract

We present a new network model accounting for multidimensional assortativity. Each node is characterized by a number of features and the probability of a link between two nodes depends on common features. We do not fix a priori the total number of possible features. The bipartite network of the nodes and the features evolves according to a stochastic dynamics that depends on three parameters that respectively regulate the preferential attachment in the transmission of the features to the nodes, the number of new features per node, and the power-law behavior of the total number of observed features. Our model also takes into account a mechanism of triadic closure. We provide theoretical results and statistical estimators for the parameters of the model. We validate our approach by means of simulations and an empirical analysis of a network of scientific collaborations.

Item Type: Article
Projects: Crisis Lab
Uncontrolled Keywords: probabilistic modeling, complex network, assortativity, preferential attachment, triadic closure.
Subjects: H Social Sciences > H Social Sciences (General)
H Social Sciences > HA Statistics
Research Area: Economics and Institutional Change
Depositing User: Irene Crimaldi
Date Deposited: 08 May 2017 12:56
Last Modified: 08 May 2017 13:02
URI: http://eprints.imtlucca.it/id/eprint/3700

Actions (login required)

Edit Item Edit Item