A game-theoretic approach for non-overlapping communities detection

In this paper, we propose a game-theoretic approach to find the community structure in complex networks based on a non-cooperative game. This approach optimizes a node-based modularity for non-overlapping communities. Experiments show that our approach is effective to discover non-overlapping communities and obtain high values of modularity and Normalized Mutual Information (NMI) for real-world and synthetic networks in a reasonable time.

[1]  Wei Chen,et al.  Community Detection in Social Networks through Community Formation Games , 2011, IJCAI.

[2]  Andrea Lancichinetti,et al.  Community detection algorithms: a comparative analysis: invited presentation, extended abstract , 2009, VALUETOOLS.

[3]  Yang Zhang,et al.  Location Prediction: Communities Speak Louder than Friends , 2014, COSN.

[4]  Noémi Gaskó,et al.  Game theory, Extremal optimization, and Community Structure Detection in Complex Networks , 2016, GECCO.

[5]  Jin Xu,et al.  Dynamic community detection based on game theory in social networks , 2015, 2015 IEEE International Conference on Big Data (Big Data).

[6]  Yang Zhang,et al.  Exploring Communities for Effective Location Prediction , 2015, WWW.

[7]  Konstantin Avrachenkov,et al.  Cooperative Game Theory Approaches for Network Partitioning , 2017, COCOON.

[8]  M E J Newman,et al.  Community structure in social and biological networks , 2001, Proceedings of the National Academy of Sciences of the United States of America.

[9]  F. Radicchi,et al.  Benchmark graphs for testing community detection algorithms. , 2008, Physical review. E, Statistical, nonlinear, and soft matter physics.

[10]  W. Zachary,et al.  An Information Flow Model for Conflict and Fission in Small Groups , 1977, Journal of Anthropological Research.

[11]  Punam Bedi,et al.  Community detection in social networks , 2016, WIREs Data Mining Knowl. Discov..

[12]  Wei Chen,et al.  A game-theoretic framework to identify overlapping communities in social networks , 2010, Data Mining and Knowledge Discovery.

[13]  D. Lusseau,et al.  The bottlenose dolphin community of Doubtful Sound features a large proportion of long-lasting associations , 2003, Behavioral Ecology and Sociobiology.

[14]  R. Albert,et al.  The large-scale organization of metabolic networks , 2000, Nature.

[15]  Lizhen Wang,et al.  A Fast Approach for Detecting Overlapping Communities in Social Networks Based on Game Theory , 2015, BICOD.

[16]  Meina Song,et al.  Book Recommendation Based on Community Detection , 2013, ICPCA/SWS.

[17]  Anca Andreica,et al.  Game Theory and Extremal Optimization for Community Detection in Complex Dynamic Networks , 2014, PloS one.

[18]  Lizhen Wang,et al.  An approach for overlapping and hierarchical community detection in social networks based on coalition formation game theory , 2015, Expert Syst. Appl..

[19]  A. Arenas,et al.  Community detection in complex networks using extremal optimization. , 2005, Physical review. E, Statistical, nonlinear, and soft matter physics.

[20]  Hamidreza Alvari,et al.  Community detection in dynamic social networks: A game-theoretic approach , 2014, 2014 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining (ASONAM 2014).

[21]  Yang Zhang,et al.  Event Prediction with Community Leaders , 2015, 2015 10th International Conference on Availability, Reliability and Security.

[22]  Tang Xianchao Lancichinetti-Fortunato-Radicchi (LFR) benchmark , 2014 .

[23]  Jean-Loup Guillaume,et al.  Fast unfolding of communities in large networks , 2008, 0803.0476.

[24]  Santo Fortunato,et al.  Community detection in networks: A user guide , 2016, ArXiv.

[25]  M E J Newman,et al.  Finding and evaluating community structure in networks. , 2003, Physical review. E, Statistical, nonlinear, and soft matter physics.

[26]  Elham Havvaei,et al.  A Game-Theoretic Approach for Detection of Overlapping Communities in Dynamic Complex Networks , 2016, ArXiv.

[27]  Burleigh B. Gardner,et al.  Deep South: A Social Anthropological Study of Caste and Class , 1942 .

[28]  Claudio Castellano,et al.  Community Structure in Graphs , 2007, Encyclopedia of Complexity and Systems Science.

[29]  A. Hamzeh,et al.  Social networks community detection using the Shapley value , 2012, The 16th CSI International Symposium on Artificial Intelligence and Signal Processing (AISP 2012).

[30]  Pablo Rodriguez,et al.  Divide and Conquer: Partitioning Online Social Networks , 2009, ArXiv.

[31]  M. Newman,et al.  Finding community structure in networks using the eigenvectors of matrices. , 2006, Physical review. E, Statistical, nonlinear, and soft matter physics.

[32]  Lihua Zhou,et al.  A Coalition Formation Game Theory-Based Approach for Detecting Communities in Multi-relational Networks , 2015, WAIM.

[33]  Y. Narahari,et al.  A game theory inspired, decentralized, local information based algorithm for community detection in social graphs , 2012, Proceedings of the 21st International Conference on Pattern Recognition (ICPR2012).

[34]  Michel Crampes,et al.  Overlapping Community Detection Optimization and Nash Equilibrium , 2014, WIMS.

[35]  Santo Fortunato,et al.  Community detection in graphs , 2009, ArXiv.

[36]  Rodica Ioana Lung,et al.  A Game Theoretic Approach to Community Detection in Social Networks , 2011, NICSO.

[37]  Mohammed Elkoutbi,et al.  LBRW: A Learning based Random Walk for Recommender Systems , 2015, Int. J. Inf. Syst. Soc. Chang..

[38]  Pablo M. Gleiser,et al.  Community Structure in Jazz , 2003, Adv. Complex Syst..

[39]  Carlo Ratti,et al.  A General Optimization Technique for High Quality Community Detection in Complex Networks , 2013, Physical review. E, Statistical, nonlinear, and soft matter physics.

[40]  Martin Rosvall,et al.  Maps of random walks on complex networks reveal community structure , 2007, Proceedings of the National Academy of Sciences.

[41]  Hamidreza Alvari,et al.  Detecting Overlapping Communities in Social Networks by Game Theory and Structural Equivalence Concept , 2011, AICI.