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A one-stage memetic algorithm for jointly detecting hierarchical and overlapping community structures in dynamic social networks

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Abstract

Social network characterizes complex relationship among individuals, which further constitute numerous various communities based on some attributes. Furthermore, multiple communities may be of a hierarchical structure, and parts of them are overlapped with each other. Additionally, as time goes by, some individuals or relations in social networks may change, so that it has been challenging to detect hierarchical and overlapping community structures in dynamical social networks. Most previous methods were based on a two-stage strategy, which firstly determines a hierarchical structure for the concerned social network, and then detects overlapping communities at each hierarchical level. However, the detection in the second stage is often restricted to the hierarchical structure determined in the first stage. As a result, this work proposes a one-stage memetic algorithm (MA) for jointly detecting hierarchical and overlapping community structures in dynamic social networks, in which a number of quality evaluation functions and constraints of community capacity as well as number of hierarchical levels are considered to enhance quality of detection. The proposed MA improves the genetic algorithm with local search and immigrant schemes. By simulation, in comparison to previous methods, the proposed MA is shown to have better quality. By visual analysis, the detected community structures look more correctly and can be explained more reasonably. Furthermore, dynamic community structures in different scenarios are analyzed in detail.

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Acknowledgements

This work has been supported in part by the National Science and Technology Council, Taiwan, under Grants NSTC 112-2221-E-A49-116-MY3, MOST 109-2221-E-009-068-MY3, MOST 111-2622-E-A49-011, and NSTC 111-2221-E-A49-081.

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Authors and Affiliations

  1. Department of Industrial Engineering and Management, National Yang Ming Chiao Tung University, Hsinchu, 300, Taiwan

    Chun-Cheng Lin, Zhen-Yin Annie Chen & Jung-Chao Wu

  2. Department of Industrial Engineering and Management, National Chin-Yi University of Technology, Taichung, 411, Taiwan

    Chun-Cheng Lin

  3. Department of Medical Research, China Medical University Hospital, China Medical University, Taichung, 404, Taiwan

    Chun-Cheng Lin

  4. Department of Information Technology, Overseas Chinese University, Taichung, 407, Taiwan

    Hui-Hsin Chin

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Lin, CC., Chin, HH., Chen, ZY.A. et al. A one-stage memetic algorithm for jointly detecting hierarchical and overlapping community structures in dynamic social networks. Wireless Netw (2023). https://doi.org/10.1007/s11276-023-03475-6

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