An improved game-theoretic approach to uncover overlapping communities

Hong-Liang Sun (), Eugene Ch’ng (), Xi Yong (), Jonathan M. Garibaldi (), Simon See and Duan-Bing Chen
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Hong-Liang Sun: NVIDIA Joint-Lab on Mixed Reality, International Doctoral Innovation Centre, The University of Nottingham, Ningbo 315100, P. R. China
Eugene Ch’ng: NVIDIA Joint-Lab on Mixed Reality, International Doctoral Innovation Centre, The University of Nottingham, Ningbo 315100, P. R. China
Xi Yong: Water Information Centre, Ministry of Water Resources, Beijing 100053, P. R. China
Jonathan M. Garibaldi: School of Computer Science, University of Nottingham, Nottingham NG8 1BB, UK
Simon See: NVIDIA AI Technology Centre, NVIDIA, Singapore 138522, Singapore5Centre for High Performance Computing, Shanghai Jiao Tong University, Shanghai 200240, P. R. China
Duan-Bing Chen: Web Sciences Center, Big Data Research Center, The Center for Digitized Culture and Media, University of Electronic Science and Technology of China, Chengdu 611731, P. R. China

International Journal of Modern Physics C (IJMPC), 2017, vol. 28, issue 09, 1-17

Abstract: 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.

Keywords: Overlapping community detection; game theory; complex networks (search for similar items in EconPapers)
Date: 2017
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (6)

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DOI: 10.1142/S0129183117501121

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