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Minimum spanning trees for community detection

Author

Listed:
  • Wu, Jianshe
  • Li, Xiaoxiao
  • Jiao, Licheng
  • Wang, Xiaohua
  • Sun, Bo

Abstract

A simple deterministic algorithm for community detection is provided by using two rounds of minimum spanning trees. By comparing the first round minimum spanning tree (1st-MST) with the second round spanning tree (2nd-MST) of the network, communities are detected and their overlapping nodes are also identified. To generate the two MSTs, a distance matrix is defined and computed from the adjacent matrix of the network. Compared with the resistance matrix or the communicability matrix used in community detection in the literature, the proposed distance matrix is very simple in computation. The proposed algorithm is tested on real world social networks, graphs which are failed by the modularity maximization, and the LFR benchmark graphs for community detection.

Suggested Citation

  • Wu, Jianshe & Li, Xiaoxiao & Jiao, Licheng & Wang, Xiaohua & Sun, Bo, 2013. "Minimum spanning trees for community detection," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 392(9), pages 2265-2277.
    • Handle: RePEc:eee:phsmap:v:392:y:2013:i:9:p:2265-2277
    DOI: 10.1016/j.physa.2013.01.015
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    References listed on IDEAS

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    1. Piccardi, Carlo & Calatroni, Lisa & Bertoni, Fabio, 2010. "Communities in Italian corporate networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 389(22), pages 5247-5258.
    2. Barigozzi, Matteo & Fagiolo, Giorgio & Mangioni, Giuseppe, 2011. "Identifying the community structure of the international-trade multi-network," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 390(11), pages 2051-2066.
    3. Huang, Jianbin & Sun, Heli & Han, Jiawei & Feng, Boqin, 2011. "Density-based shrinkage for revealing hierarchical and overlapping community structure in networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 390(11), pages 2160-2171.
    4. Xie, Fuding & Ji, Min & Zhang, Yong & Huang, Dan, 2009. "The detection of community structure in network via an improved spectral method," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 388(15), pages 3268-3272.
    5. Gregory, Steve, 2012. "Ordered community structure in networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 391(8), pages 2752-2763.
    6. Wu, Jianshe & Lu, Rui & Jiao, Licheng & Liu, Fang & Yu, Xin & Wang, Da & Sun, Bo, 2013. "Phase transition model for community detection," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 392(6), pages 1287-1301.
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    Cited by:

    1. Ding, Jingyi & Jiao, Licheng & Wu, Jianshe & Hou, Yunting & Qi, Yutao, 2015. "Prediction of missing links based on multi-resolution community division," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 417(C), pages 76-85.

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