Weighted Multiplex Networks
Editors
Menichetti, G
Remondini, D
Panzarasa, P
Mondragon, RJ
Bianconi, G
Volume
9
Pagination
e97857 - ?
Publisher
Publisher URL
DOI
10.1371/journal.pone.0097857
Journal
PLoS One
Issue
ISSN
1932-6203
Metadata
Show full item recordAbstract
One of the most important challenges in network science is to quantify the information encoded in complex network structures. Disentangling randomness from organizational principles is even more demanding when networks have a multiplex nature. Multiplex networks are multilayer systems of nodes that can be linked in multiple interacting and co-evolving layers. In these networks, relevant information might not be captured if the single layers were analyzed separately. Here we demonstrate that such partial analysis of layers fails to capture significant correlations between weights and topology of complex multiplex networks. To this end, we study two weighted multiplex co-authorship and citation networks involving the authors included in the American Physical Society. We show that in these networks weights are strongly correlated with multiplex structure, and provide empirical evidence in favor of the advantage of studying weighted measures of multiplex networks, such as multistrength and the inverse multiparticipation ratio. Finally, we introduce a theoretical framework based on the entropy of multiplex ensembles to quantify the information stored in multiplex networks that would remain undetected if the single layers were analyzed in isolation
Authors
Menichetti, GCollections
- Mathematics [1444]