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Community detection based on network communicability distance

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  • Xu, Ying

Abstract

Community detection in complex networks is a topic of high interest in many fields. In this paper, we propose a new algorithm based on communicability distance for community detection in network(CD algorithm). Furthermore, the accuracy and efficiency of this algorithm are tested by some representative real-world networks and computer-generated networks(GN networks). The experimental results indicate that the CD algorithm can accurately and effectively detect the community structure in these networks with higher values of modularity.

Suggested Citation

  • Xu, Ying, 2019. "Community detection based on network communicability distance," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 515(C), pages 112-118.
    • Handle: RePEc:eee:phsmap:v:515:y:2019:i:c:p:112-118
    DOI: 10.1016/j.physa.2018.09.191
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    References listed on IDEAS

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    1. Pablo M. Gleiser & Leon Danon, 2003. "Community Structure In Jazz," Advances in Complex Systems (ACS), World Scientific Publishing Co. Pte. Ltd., vol. 6(04), pages 565-573.
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    Cited by:

    1. Xu, Ying, 2020. "A spectral method to detect community structure based on the communicability modularity," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 537(C).

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