A fast and reasonable method for community detection with adjustable extent of overlapping

Communities exist in complex networks of different areas, and in some cases they may overlap between each other. Community detection is a good way to understand the structure, function and evolution of complex networks. There have been some methods to find disjoint or overlapping communities. While most of these methods only fit one single situation, disjoint or overlapping. In our opinion, it is unreasonable to find disjoint communities on a network with clear overlap or to find overlapping communities on a network without any visible overlapping node. In this paper, we propose a link partition based method which can find communities with adjustable extent of overlapping according to backgrounds of specific applications or personal preferences. Experimental results on some real-world networks show that our method can find reasonable communities with adjustable extent of overlapping, and is suitable for networks with high densities and large scales.

[1]  Lada A. Adamic,et al.  The political blogosphere and the 2004 U.S. election: divided they blog , 2005, LinkKDD '05.

[2]  Jure Leskovec,et al.  Community Structure in Large Networks: Natural Cluster Sizes and the Absence of Large Well-Defined Clusters , 2008, Internet Math..

[3]  M. Newman,et al.  Finding community structure in very large networks. , 2004, Physical review. E, Statistical, nonlinear, and soft matter physics.

[4]  Steve Gregory,et al.  A Fast Algorithm to Find Overlapping Communities in Networks , 2008, ECML/PKDD.

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

[6]  M E J Newman,et al.  Fast algorithm for detecting community structure in networks. , 2003, Physical review. E, Statistical, nonlinear, and soft matter physics.

[7]  V. Carchiolo,et al.  Extending the definition of modularity to directed graphs with overlapping communities , 2008, 0801.1647.

[8]  Christos Faloutsos,et al.  Graph evolution: Densification and shrinking diameters , 2006, TKDD.

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

[10]  Steve Gregory,et al.  An Algorithm to Find Overlapping Community Structure in Networks , 2007, PKDD.

[11]  R. Lambiotte,et al.  Line graphs, link partitions, and overlapping communities. , 2009, Physical review. E, Statistical, nonlinear, and soft matter physics.

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

[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]  Albert-László Barabási,et al.  Statistical mechanics of complex networks , 2001, ArXiv.

[15]  S. Strogatz Exploring complex networks , 2001, Nature.

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

[17]  Mark Newman,et al.  Detecting community structure in networks , 2004 .

[18]  T. Vicsek,et al.  Uncovering the overlapping community structure of complex networks in nature and society , 2005, Nature.