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An improved label propagation algorithm using average node energy in complex networks

Author

Listed:
  • Peng, Hao
  • Zhao, Dandan
  • Li, Lin
  • Lu, Jianfeng
  • Han, Jianmin
  • Wu, Songyang

Abstract

Detecting overlapping community structure can give a significant insight into structural and functional properties in complex networks. In this Letter, we propose an improved label propagation algorithm (LPA) to uncover overlapping community structure. After mapping nodes into random variables, the algorithm calculates variance of each node and the proposed average node energy. The nodes whose variances are less than a tunable threshold are regarded as bridge nodes and meanwhile changing the given threshold can uncover some latent bridge node. Simulation results in real-world and artificial networks show that the improved algorithm is efficient in revealing overlapping community structures.

Suggested Citation

  • Peng, Hao & Zhao, Dandan & Li, Lin & Lu, Jianfeng & Han, Jianmin & Wu, Songyang, 2016. "An improved label propagation algorithm using average node energy in complex networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 460(C), pages 98-104.
    • Handle: RePEc:eee:phsmap:v:460:y:2016:i:c:p:98-104
    DOI: 10.1016/j.physa.2016.04.042
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    Citations

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    Cited by:

    1. Garza, Sara E. & Schaeffer, Satu Elisa, 2019. "Community detection with the Label Propagation Algorithm: A survey," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 534(C).
    2. Sun, Hong-liang & Ch’ng, Eugene & Yong, Xi & Garibaldi, Jonathan M. & See, Simon & Chen, Duan-bing, 2018. "A fast community detection method in bipartite networks by distance dynamics," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 496(C), pages 108-120.

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