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Balanced Multi-Label Propagation for Overlapping Community Detection in Social Networks

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Abstract

In this paper, we propose a balanced multi-label propagation algorithm (BMLPA) for overlapping community detection in social networks. As well as its fast speed, another important advantage of our method is good stability, which other multi-label propagation algorithms, such as COPRA, lack. In BMLPA, we propose a new update strategy, which requires that community identifiers of one vertex should have balanced belonging coefficients. The advantage of this strategy is that it allows vertices to belong to any number of communities without a global limit on the largest number of community memberships, which is needed for COPRA. Also, we propose a fast method to generate “rough cores”, which can be used to initialize labels for multi-label propagation algorithms, and are able to improve the quality and stability of results. Experimental results on synthetic and real social networks show that BMLPA is very efficient and effective for uncovering overlapping communities.

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Authors and Affiliations

  1. School of Computer and Information Technology, Beijing Jiaotong University, Beijing, 100044, China

    Zhi-Hao Wu, You-Fang Lin, Huai-Yu Wan (Student Member, CCF) & Sheng-Feng Tian

  2. Department of Computer Science, University of Bristol, Bristol, BS8 1UB, U.K.

    Steve Gregory

Authors
  1. Zhi-Hao Wu
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  2. You-Fang Lin
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  3. Steve Gregory
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  4. Huai-Yu Wan
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  5. Sheng-Feng Tian
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Corresponding author

Correspondence to Zhi-Hao Wu.

Additional information

This work was partially supported by the Fundamental Research Funds for the Central Universities of China, the National Natural Science Foundation of China under Grant No. 60905029, the Natural Science Foundation of Beijing of China under Grant No. 4112046.

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Wu, ZH., Lin, YF., Gregory, S. et al. Balanced Multi-Label Propagation for Overlapping Community Detection in Social Networks. J. Comput. Sci. Technol. 27, 468–479 (2012). https://doi.org/10.1007/s11390-012-1236-x

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  • DOI: https://doi.org/10.1007/s11390-012-1236-x

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