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Detecting Overlapping Communities in Complex Networks: An Evolutionary Label Propagation Approach

Author

Listed:
  • Mojtaba Saif

    (CSE and IT Department, Shiraz University, Shiraz, Fars, Iran)

  • Mohammad Ebrahim Samie

    (��Department of Computer Engineering and IT, Jahrom University, Jahrom, Fars, Iran)

  • Ali Hamzeh

    (CSE and IT Department, Shiraz University, Shiraz, Fars, Iran)

Abstract

A challenging issue in complex network analysis is overlapping community detection, which has attracted many studies. Label Propagation Algorithm (LPA) is one of the famous studies to detect communities. But it has some weaknesses such as using local information and randomly choosing the sequences of processing nodes. We introduce Evolutionary Label Propagation Algorithm (ELPA) to solve these problems and improve accuracy. ELPA uses an intelligent search instead of randomly processing nodes and fuses local and global perspectives. The proposed ELPA is compared with several state-of-the-art algorithms on synthetic and real-world networks with different sizes, densities, and complexities. The results indicate that ELPA provides better results on most of the test instances. Therefore, ELPA is an accurate and efficient algorithm for detecting overlapping communities.

Suggested Citation

  • Mojtaba Saif & Mohammad Ebrahim Samie & Ali Hamzeh, 2024. "Detecting Overlapping Communities in Complex Networks: An Evolutionary Label Propagation Approach," International Journal of Information Technology & Decision Making (IJITDM), World Scientific Publishing Co. Pte. Ltd., vol. 23(01), pages 327-360, January.
    • Handle: RePEc:wsi:ijitdm:v:23:y:2024:i:01:n:s0219622023500062
    DOI: 10.1142/S0219622023500062
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