TY  - JOUR
TI  - Cluster analysis of weighted bipartite networks: a new copula-based approach
ID  - eprints2324
AV  - public
N2  - 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.
JF  - PloS One
IS  - 10
UR  - http://dx.doi.org/10.1371/journal.pone.0109507
PB  - Public Library of Science
VL  - 9
SN  - 1932-6203
A1  - Chessa, Alessandro
A1  - Crimaldi, Irene
A1  - Riccaboni, Massimo
A1  - Trapin, Luca
Y1  - 2014/10//
ER  -