Community Detection from Bipartite Networks

Community detection from networks is one of the important and challenging research topics of social network analysis, especially from bipartite networks. In this paper, we propose an algorithm for detecting communities from bipartite networks based on ant colony optimization. Such an algorithm allows many-to-many correspondence between different types of communities. Experimental results demonstrate that our algorithm can extract multi-facet communities from bipartite networks and obtain high quality of partitioning communities.

[1]  A. Barabasi,et al.  Network biology: understanding the cell's functional organization , 2004, Nature Reviews Genetics.

[2]  Chen Wen-qin.  Research in Disease-Gene Network Based on Bipartite Network Projection , 2009 .

[3]  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.

[4]  Z. Di,et al.  Clustering coefficient and community structure of bipartite networks , 2007, 0710.0117.

[5]  Réka Albert,et al.  Near linear time algorithm to detect community structures in large-scale networks. , 2007, Physical review. E, Statistical, nonlinear, and soft matter physics.

[6]  Claudio Castellano,et al.  Defining and identifying communities in networks. , 2003, Proceedings of the National Academy of Sciences of the United States of America.

[7]  Bin Wu,et al.  Overlapping Community Detection in Bipartite Networks , 2008, 2008 IEEE/WIC/ACM International Conference on Web Intelligence and Intelligent Agent Technology.

[8]  Marco Dorigo,et al.  Ant system: optimization by a colony of cooperating agents , 1996, IEEE Trans. Syst. Man Cybern. Part B.

[9]  He Da-ren.  An Empirical Statistical Investigation on Chinese Mainland Movie Network , 2007 .

[10]  Duncan J. Watts,et al.  Collective dynamics of ‘small-world’ networks , 1998, Nature.

[11]  Tsuyoshi Murata,et al.  Detecting Communities from Bipartite Networks Based on Bipartite Modularities , 2009, 2009 International Conference on Computational Science and Engineering.

[12]  M E Newman,et al.  Scientific collaboration networks. I. Network construction and fundamental results. , 2001, Physical review. E, Statistical, nonlinear, and soft matter physics.

[13]  M. Newman,et al.  Scientific collaboration networks. II. Shortest paths, weighted networks, and centrality. , 2001, Physical review. E, Statistical, nonlinear, and soft matter physics.

[14]  Ken Wakita,et al.  Extracting Multi-facet Community Structure from Bipartite Networks , 2009, 2009 International Conference on Computational Science and Engineering.

[15]  John Scott,et al.  The Anatomy of Scottish Capital: Scottish Companies and Scottish Capital, 1900-1979 , 1980 .

[16]  Andrei Z. Broder,et al.  Graph structure in the Web , 2000, Comput. Networks.

[17]  Tsuyoshi Murata,et al.  How Does Label Propagation Algorithm Work in Bipartite Networks? , 2009, 2009 IEEE/WIC/ACM International Joint Conference on Web Intelligence and Intelligent Agent Technology.

[18]  M Ausloos,et al.  Uncovering collective listening habits and music genres in bipartite networks. , 2005, Physical review. E, Statistical, nonlinear, and soft matter physics.

[19]  M. Barber.  Modularity and community detection in bipartite networks. , 2007, Physical review. E, Statistical, nonlinear, and soft matter physics.

[20]  Roger Guimerà,et al.  Module identification in bipartite and directed networks. , 2007, Physical review. E, Statistical, nonlinear, and soft matter physics.

[21]  Mason A. Porter,et al.  Communities in Networks , 2009, ArXiv.

[22]  G. Ergun.  Human Sexual Contact Network as a Bipartite Graph , 2001, cond-mat/0111323.

[23]  S. Battiston,et al.  Statistical properties of corporate board and director networks , 2004 .

[24]  M E J Newman,et al.  Modularity and community structure in networks. , 2006, Proceedings of the National Academy of Sciences of the United States of America.

[25]  S. Lehmann,et al.  Biclique communities. , 2007, Physical review. E, Statistical, nonlinear, and soft matter physics.

[26]  Garry Robins,et al.  Small Worlds Among Interlocking Directors: Network Structure and Distance in Bipartite Graphs , 2004, Comput. Math. Organ. Theory.

[27]  Fan Ying.  A CLUSTERING ALGORITHM FOR BIPARTITE NETWORK BASED ON DISTRIBUTION MATRIX OF RESOURCES , 2010 .

[28]  Jean-Loup Guillaume,et al.  Clustering in P2P Exchanges and Consequences on Performances , 2005, IPTPS.

[29]  Tsuyoshi Murata,et al.  Community Detection in Large-scale Bipartite Networks , 2010 .