Community detection in multiplex social networks

Community detection has emerged rapidly as an important problem for many years. Although a large number of methods for this problem have been proposed, none of them address directly the problem for multiplex Online Social Networks (OSNs) in which a user can have multiple accounts in different networks. In this paper, we propose and compare two classes of approaches named Unifying Approach and Coupling Approach for community detection in multiplex OSNs. Moreover, we develop for each class a specialized NMF-based algorithm. For testing purposes, we extend the LFR benchmark to generate multiplex OSNs. Our intensive experiments show the significant improvement of our methods over the naive approach of finding community structure (CS) in each network separately.