Comparative definition of community and corresponding identifying algorithm.

A comparative definition for community in networks is proposed, and the corresponding detecting algorithm is given. A community is defined as a set of nodes, which satisfies the requirement that each node's degree inside the community should not be smaller than the node's degree toward any other community. In the algorithm, the attractive force of a community to a node is defined as the connections between them. Then employing an attractive-force-based self-organizing process, without any extra parameter, the best communities can be detected. Several artificial and real-world networks, including the Zachary karate club, college football, and large scientific collaboration networks, are analyzed. The algorithm works well in detecting communities, and it also gives a nice description of network division and group formation.

[1]  Leon Danon,et al.  Comparing community structure identification , 2005, cond-mat/0505245.

[2]  R. Rosenfeld Nature , 2009, Otolaryngology--head and neck surgery : official journal of American Academy of Otolaryngology-Head and Neck Surgery.

[3]  U. Brandes,et al.  Maximizing Modularity is hard , 2006, physics/0608255.

[4]  P. Sopp Cluster analysis. , 1996, Veterinary immunology and immunopathology.

[5]  John Scott What is social network analysis , 2010 .

[6]  Lars Kai Hansen,et al.  Deterministic modularity optimization , 2007 .