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Eigenvectors of network complement reveal community structure more accurately

Author

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  • Zarei, Mina
  • Samani, Keivan Aghababaei

Abstract

We propose a general spectral method to find communities of a network based on network complement and anti-community concepts. Analytical and numerical results show that the eigenspace of matrices corresponding to a network complement reveals the community structure of a network more accurately than the eigenspace of matrices corresponding to the network itself. It is shown that the Laplacian eigenspace is the best candidate for spectral community detection especially in networks with a heterogeneous community structure. The method is applied to some computer-generated and real-world networks with known community structures.

Suggested Citation

  • Zarei, Mina & Samani, Keivan Aghababaei, 2009. "Eigenvectors of network complement reveal community structure more accurately," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 388(8), pages 1721-1730.
    • Handle: RePEc:eee:phsmap:v:388:y:2009:i:8:p:1721-1730
    DOI: 10.1016/j.physa.2009.01.007
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    Cited by:

    1. Ausloos, Marcel & Saeedian, Meghdad & Jamali, Tayeb & Farahani, S. Vasheghani & Jafari, G. Reza, 2017. "How visas shape and make visible the geopolitical architecture of the planet," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 484(C), pages 267-275.
    2. Zhang, Dawei & Xie, Fuding & Zhang, Yong & Dong, Fangyan & Hirota, Kaoru, 2010. "Fuzzy analysis of community detection in complex networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 389(22), pages 5319-5327.

    More about this item

    Keywords

    Complex networks; Communities;

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