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Advanced modularity-specialized label propagation algorithm for detecting communities in networks

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  • Liu, X.
  • Murata, T.

Abstract

A modularity-specialized label propagation algorithm (LPAm) for detecting network communities was recently proposed. This promising algorithm offers some desirable qualities. However, LPAm favors community divisions where all communities are similar in total degree and thus it is prone to get stuck in poor local maxima in the modularity space. To escape local maxima, we employ a multistep greedy agglomerative algorithm (MSG) that can merge multiple pairs of communities at a time. Combining LPAm and MSG, we propose an advanced modularity-specialized label propagation algorithm (LPAm+). Experiments show that LPAm+ successfully detects communities with higher modularity values than ever reported in two commonly used real-world networks. Moreover, LPAm+ offers a fair compromise between accuracy and speed.

Suggested Citation

  • Liu, X. & Murata, T., 2010. "Advanced modularity-specialized label propagation algorithm for detecting communities in networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 389(7), pages 1493-1500.
    • Handle: RePEc:eee:phsmap:v:389:y:2010:i:7:p:1493-1500
    DOI: 10.1016/j.physa.2009.12.019
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    References listed on IDEAS

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    1. 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.
    2. Medus, A. & Acuña, G. & Dorso, C.O., 2005. "Detection of community structures in networks via global optimization," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 358(2), pages 593-604.
    3. G. Agarwal & D. Kempe, 2008. "Modularity-maximizing graph communities via mathematical programming," The European Physical Journal B: Condensed Matter and Complex Systems, Springer;EDP Sciences, vol. 66(3), pages 409-418, December.
    4. H. Jeong & B. Tombor & R. Albert & Z. N. Oltvai & A.-L. Barabási, 2000. "The large-scale organization of metabolic networks," Nature, Nature, vol. 407(6804), pages 651-654, October.
    5. G. Xu & S. Tsoka & L. G. Papageorgiou, 2007. "Finding community structures in complex networks using mixed integer optimisation," The European Physical Journal B: Condensed Matter and Complex Systems, Springer;EDP Sciences, vol. 60(2), pages 231-239, November.
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    2. Aghaalizadeh, Saeid & Afshord, Saeid Taghavi & Bouyer, Asgarali & Anari, Babak, 2021. "A three-stage algorithm for local community detection based on the high node importance ranking in social networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 563(C).
    3. Chuanjun Zhao & Suge Wang & Deyu Li, 2016. "Determining Fuzzy Membership for Sentiment Classification: A Three-Layer Sentiment Propagation Model," PLOS ONE, Public Library of Science, vol. 11(11), pages 1-32, November.
    4. Laassem, Brahim & Idarrou, Ali & Boujlaleb, Loubna & Iggane, M’bark, 2022. "Label propagation algorithm for community detection based on Coulomb’s law," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 593(C).
    5. Sun, Heli & Liu, Jiao & Huang, Jianbin & Wang, Guangtao & Yang, Zhou & Song, Qinbao & Jia, Xiaolin, 2015. "CenLP: A centrality-based label propagation algorithm for community detection in networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 436(C), pages 767-780.
    6. Shang, Ronghua & Zhang, Weitong & Jiao, Licheng & Stolkin, Rustam & Xue, Yu, 2017. "A community integration strategy based on an improved modularity density increment for large-scale networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 469(C), pages 471-485.
    7. Fang, Wenyi & Wang, Xin & Liu, Longzhao & Wu, Zhaole & Tang, Shaoting & Zheng, Zhiming, 2022. "Community detection through vector-label propagation algorithms," Chaos, Solitons & Fractals, Elsevier, vol. 158(C).
    8. Lin, Zhen & Zheng, Xiaolin & Xin, Nan & Chen, Deren, 2014. "CK-LPA: Efficient community detection algorithm based on label propagation with community kernel," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 416(C), pages 386-399.
    9. Wang, Zuxi & Li, Qingguang & Xiong, Wei & Jin, Fengdong & Wu, Yao, 2016. "Fast community detection based on sector edge aggregation metric model in hyperbolic space," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 452(C), pages 178-191.
    10. 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).
    11. Li, Wei & Huang, Ce & Wang, Miao & Chen, Xi, 2017. "Stepping community detection algorithm based on label propagation and similarity," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 472(C), pages 145-155.
    12. Rizman Žalik, Krista & Žalik, Borut, 2014. "A local multiresolution algorithm for detecting communities of unbalanced structures," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 407(C), pages 380-393.
    13. Shang, Ronghua & Luo, Shuang & Li, Yangyang & Jiao, Licheng & Stolkin, Rustam, 2015. "Large-scale community detection based on node membership grade and sub-communities integration," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 428(C), pages 279-294.

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