Community detection using constrained label propagation algorithm with nodes exemption

Abstract

The detection of community structure plays an important role in understanding the properties and characteristics of complex networks. The label propagation algorithm (LPA) emerges as a popular community detection method, due to its simplicity and low computational cost. Nonetheless, the LPA is not without its limitations so that the Semi Synchronous Constrained Label Propagation Algorithm (SSCLPA) is a modified LPA that implements various constraints to ameliorate the stability of the LPA. Aside from giving accurate and deterministic detection, it can avoid trivial detection. In this paper the SSCLPA is extended into weighted and directed networks, so that nodes which fulfill certain conditions are updated separately at the end of the algorithm. Furthermore, some modifications are performed on the propagation processes in the SSCLPA. These new features and modifications improve the time efficiency of the SSCLPA with only marginal loss in the quality of the detection. Our proposed method is tested and compared to the other community detection methods in various benchmark and real-world networks. The results showed that the proposed method is a well-balanced method with features that takes into account the stability, quality and time efficiency of the detection.

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Acknowledgements

The authors would like to acknowledge Professor Michael Brunger of Flinder University for his careful reading of the paper and for some useful suggestions. This project is supported by University of Malaya HIR Grant UM.C/625/1/HIR/MOHE/SC/13. J.H.C. also wants to acknowledge the support of University of Malaya HIR GRAS.

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Correspondence to Jia Hou Chin.

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Chin, J.H., Ratnavelu, K. Community detection using constrained label propagation algorithm with nodes exemption. Computing (2021). https://doi.org/10.1007/s00607-021-00966-2

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Keywords

  • Complex networks
  • Community structure
  • Community detection
  • Label propagation algorithm

Mathematics Subject Classification

  • 05C82
  • 05C85