eprintid: 2189
rev_number: 20
eprint_status: archive
userid: 6
dir: disk0/00/00/21/89
datestamp: 2014-04-10 12:19:02
lastmod: 2014-10-27 10:46:30
status_changed: 2014-04-14 09:52:06
type: monograph
metadata_visibility: show
creators_name: Chessa, Alessandro
creators_name: Crimaldi, Irene
creators_name: Riccaboni, Massimo
creators_name: Trapin, Luca
creators_id: alessandro.chessa@imtlucca.it
creators_id: irene.crimaldi@imtlucca.it
creators_id: massimo.riccaboni@imtlucca.it
creators_id: luca.trapin@imtlucca.it
title: Cluster analysis of weighted bipartite networks: a new copula-based approach
ispublished: pub
subjects: HB
subjects: QA
divisions: EIC
full_text_status: public
monograph_type: imt_eic_working_paper
keywords: clustering, complex network, copula function, positional analysis, weighted bipartite network.
note: Published in PloS One (ISSN 1932-6203): http://dx.doi.org/10.1371/journal.pone.0109507
abstract: 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. 
date: 2014-04
number: 3
publisher: IMT Institute for Advanced Studies Lucca
pages: 22
institution: IMT Institute for Advanced Studies Lucca
related_url_url: http://dx.doi.org/10.1371/journal.pone.0109507
projects: Project “CRISIS Lab” 
citation:   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         
document_url: http://eprints.imtlucca.it/2189/1/EIC_WP_3_2014.pdf