relation: http://eprints.imtlucca.it/3700/
title: Modeling networks with a growing feature-structure
creator: Crimaldi, Irene
creator: Del Vicario, Michela
creator: Morrison, Greg
creator: Quattrociocchi, Walter
creator: Riccaboni, Massimo
subject: H Social Sciences (General)
subject: HA Statistics
description: 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.
publisher: Tohoku University. Graduate School of Information Sciences
date: 2017
type: Article
type: PeerReviewed
identifier:   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, 23 (2).  pp. 127-144.  ISSN 1340-9050      (2017)  
relation: https://www.is.tohoku.ac.jp/en/iis/