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A spectral method to detect community structure based on the communicability modularity

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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 the communicability of vertices, rather than the most weakly connected vertex pairs or a number of edges between communities. 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 proposed algorithm can accurately and effectively detect the community structure in these networks with higher values of modularity.

Suggested Citation

  • 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).
    • Handle: RePEc:eee:phsmap:v:537:y:2020:i:c:s037843711931564x
    DOI: 10.1016/j.physa.2019.122751
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    References listed on IDEAS

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    1. Mehrle, David & Strosser, Amy & Harkin, Anthony, 2015. "Walk-modularity and community structure in networks," Network Science, Cambridge University Press, vol. 3(3), pages 348-360, September.
    2. David Liben‐Nowell & Jon Kleinberg, 2007. "The link‐prediction problem for social networks," Journal of the American Society for Information Science and Technology, Association for Information Science & Technology, vol. 58(7), pages 1019-1031, May.
    3. 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.
    4. Xu, Ying, 2019. "Community detection based on network communicability distance," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 515(C), pages 112-118.
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    Cited by:

    1. Agrawal, Smita & Patel, Atul, 2021. "SAG Cluster: An unsupervised graph clustering based on collaborative similarity for community detection in complex networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 563(C).

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