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Cluster analysis of weighted bipartite networks: a new copula-based approach

Chessa, Alessandro and Crimaldi, Irene and Riccaboni, Massimo and Trapin, Luca Cluster analysis of weighted bipartite networks: a new copula-based approach. PloS One, 9 (10). e109507. ISSN 1932-6203 (2014)

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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. 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. Moreover, 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.

Item Type: Article
Identification Number: https://doi.org/10.1371/journal.pone.0109507
Projects: FIRB project RBFR12BA3Y, CNR PNR Project “CRISIS Lab”
Subjects: H Social Sciences > HB Economic Theory
Q Science > QA Mathematics
Research Area: Economics and Institutional Change
Depositing User: Ms T. Iannizzi
Date Deposited: 14 Oct 2014 09:21
Last Modified: 27 Oct 2014 10:33
URI: http://eprints.imtlucca.it/id/eprint/2324

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