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Towards Linear Time Overlapping Community Detection in Social Networks

  • Jierui Xie
  • Boleslaw K. Szymanski
Part of the Lecture Notes in Computer Science book series (LNCS, volume 7302)

Abstract

Membership diversity is a characteristic aspect of social networks in which a person may belong to more than one social group. For this reason, discovering overlapping structures is necessary for realistic social analysis. In this paper, we present a fast algorithm, called SLPA, for overlapping community detection in large-scale networks. SLPA spreads labels according to dynamic interaction rules. It can be applied to both unipartite and bipartite networks. It is also able to uncover overlapping nested hierarchy. The time complexity of SLPA scales linearly with the number of edges in the network. Experiments in both synthetic and real-world networks show that SLPA has an excellent performance in identifying both node and community level overlapping structures.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2012

Authors and Affiliations

  • Jierui Xie
    • 1
  • Boleslaw K. Szymanski
    • 1
  1. 1.Rensselaer Polytechnic InstituteTroyUSA

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