relation: http://eprints.imtlucca.it/2189/
title: Cluster analysis of weighted bipartite networks: a new copula-based approach
creator: Chessa, Alessandro
creator: Crimaldi, Irene
creator: Riccaboni, Massimo
creator: Trapin, Luca
subject: HB Economic Theory
subject: QA Mathematics
description: In this work we are interested in identifying clusters of "positional equivalent" actors, i.e. actors who play a similar role in a system. In particular, we analyze weighted bipartite networks that describes the relationships between actors on one side and features or traits on the other, together with the intensity level to which actors show their features. The main contribution of our work is twofold. First, we develop a methodological approach that takes into account the underlying multivariate dependence among groups of actors. The idea is that positions in a network could be defined on the basis of the similar intensity levels that the actors exhibit in expressing some features, instead of just considering relationships that actors hold with each others. Second, we propose a new clustering procedure that exploits the potentiality of copula functions, a mathematical instrument for the modelization of the stochastic dependence structure. Our clustering algorithm can be applied both to binary and real-valued matrices. We validate it with simulations and applications to real-world data. 
publisher: IMT Institute for Advanced Studies Lucca
date: 2014-04
type: Working Paper
type: NonPeerReviewed
format: application/pdf
language: en
identifier: http://eprints.imtlucca.it/2189/1/EIC_WP_3_2014.pdf
identifier:   Chessa, Alessandro and Crimaldi, Irene and Riccaboni, Massimo and Trapin, Luca  Cluster analysis of weighted bipartite networks: a new copula-based approach.  EIC working paper series  #3/2014    IMT Institute for Advanced Studies Lucca