Literature DB >> 18850911

Comparative definition of community and corresponding identifying algorithm.

Yanqing Hu1, Hongbin Chen, Peng Zhang, Menghui Li, Zengru Di, Ying Fan.   

Abstract

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.

Year:  2008        PMID: 18850911     DOI: 10.1103/PhysRevE.78.026121

Source DB:  PubMed          Journal:  Phys Rev E Stat Nonlin Soft Matter Phys        ISSN: 1539-3755


  5 in total

1.  Finding and testing network communities by lumped Markov chains.

Authors:  Carlo Piccardi
Journal:  PLoS One       Date:  2011-11-03       Impact factor: 3.240

2.  Discovering link communities in complex networks by an integer programming model and a genetic algorithm.

Authors:  Zhenping Li; Xiang-Sun Zhang; Rui-Sheng Wang; Hongwei Liu; Shihua Zhang
Journal:  PLoS One       Date:  2013-12-30       Impact factor: 3.240

3.  A seed-expanding method based on random walks for community detection in networks with ambiguous community structures.

Authors:  Yansen Su; Bangju Wang; Xingyi Zhang
Journal:  Sci Rep       Date:  2017-02-03       Impact factor: 4.379

4.  Approximation of Nash equilibria and the network community structure detection problem.

Authors:  Suciu Mihai-Alexandru; Gaskó Noémi; Lung Rodica Ioana
Journal:  PLoS One       Date:  2017-05-03       Impact factor: 3.240

5.  Multi-resolution community detection in massive networks.

Authors:  Jihui Han; Wei Li; Weibing Deng
Journal:  Sci Rep       Date:  2016-12-13       Impact factor: 4.379

  5 in total

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