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Using Coalitional Games to Detect Communities in Social Networks

  • Lihua Zhou
  • Chao Cheng
  • Kevin Lü
  • Hongmei Chen
Part of the Lecture Notes in Computer Science book series (LNCS, volume 7923)

Abstract

The community detection in social networks is important to understand the structural and functional properties of networks. In this paper we propose a coalitional game model for community detection in social networks, and use the Shapley Value in coalitional games to evaluate each individual’s contribution to the closeness of connection. We then develop an iterative formula for computing the Shapley Value to improve the computation efficiency. We further propose a hierarchical clustering algorithm GAMEHC to detect communities in social networks. The effectiveness of our methods is verified by preliminary experimental result.

Keywords

social networks community detection game theory 

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Copyright information

© Springer-Verlag Berlin Heidelberg 2013

Authors and Affiliations

  • Lihua Zhou
    • 1
  • Chao Cheng
    • 1
  • Kevin Lü
    • 2
  • Hongmei Chen
    • 1
  1. 1.Department of Computer Science and EngineeringYunnan UniversityKunmingChina
  2. 2.Brunel UniversityUxbridgeUK

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