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An improved game-theoretic approach to uncover overlapping communities

Sun, Hong-Liang; Ch'ng, Eugene; Yong, Xi; Garibaldi, Jonathan M.; See, Simon; Chen, Duan-Bing


Hong-Liang Sun

Eugene Ch'ng

Xi Yong

Simon See

Duan-Bing Chen


How can we uncover overlapping communities from complex networks to understand the inherent structures and functions? Chen et al. firstly proposed a community game (Game) to study this problem, and the overlapping communities have been discovered when the game is convergent. It is based on the assumption that each vertex of the underlying network is a rational game player to maximize its utility. In this paper, we investigate how similar vertices affect the formation of community game. The Adamic–Adar Index (AA Index) has been employed to define the new utility function. This novel method has been evaluated on both synthetic and real-world networks. Experimental study shows that it has significant improvement of accuracy (from 4.8% to 37.6%) compared with the Game on 10 real networks. It is more efficient on Facebook networks (FN) and Amazon co-purchasing networks than on other networks. This result implicates that “friend circles of friends” of Facebook are valuable to understand the overlapping community division.

Journal Article Type Article
Acceptance Date Aug 21, 2017
Publication Date Sep 7, 2017
Deposit Date Oct 3, 2017
Publicly Available Date Sep 8, 2018
Journal International Journal of Modern Physics C
Print ISSN 0129-1831
Electronic ISSN 1793-6586
Publisher World Scientific
Peer Reviewed Peer Reviewed
Volume 28
Issue 8
Article Number 1750112
Keywords Overlapping community detection; game theory; complex networks
Public URL
Publisher URL
Additional Information Electronic version of an article published as International Journal of Modern Physics C, Volume 28, Issue 8, 2017, pp.1-17 doi:10.1142/S0129183117501121 © World Scientific Publishing Company,


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