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Direct Comparative Analysis of Nature-Inspired Optimization Algorithms on Community Detection Problem in Social Networks

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Mobile Computing and Sustainable Informatics

Part of the book series: Lecture Notes on Data Engineering and Communications Technologies ((LNDECT,volume 166))

Abstract

Nature-inspired optimization Algorithms (NIOAs) are nowadays a popular choice for community detection in social networks. Community detection problem in social network is treated as an optimization problem, where the objective is to either maximize the connection within the community or minimize connections between the communities. To apply NIOAs, either of the two, or both objectives are explored. Since NIOAs mostly exploit randomness in their strategies, it is necessary to analyze their performance for specific applications. In this paper, NIOAs are analyzed for the community detection problem. A direct comparison approach is followed to perform the pairwise comparison of NIOAs. The performance is measured in terms of five scores designed based on the prasatul matrix and also with average isolability. Three widely used real-world social networks and four NIOAs are considered for analyzing the quality of communities generated by NIOAs.

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Acknowledgements

This research work is supported by the Science and Engineering Board (SERB), Department of Science and Technology (DST) of the Government of India under Grant No. EEQ/2019/000657.

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Authors and Affiliations

  1. Department of Computer Science and Engineering, National Institute of Technology, Silchar, 788010, Assam, India

    Soumita Das, Bijita Singha & Anupam Biswas

  2. Université Paris-Saclay, INRAE, UMR 518 MIA, Palaiseau, France

    Alberto Tonda

Authors
  1. Soumita Das
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  2. Bijita Singha
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  3. Alberto Tonda
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  4. Anupam Biswas
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Corresponding author

Correspondence to Soumita Das .

Editor information

Editors and Affiliations

  1. Pulchowk Campus, Tribhuvan University, Kathmandu, Nepal

    Subarna Shakya

  2. Department of Computer Science, International Hellenic University, Kavala, Greece

    George Papakostas

  3. Computer Science Department, Texas Southern University, Houston, TX, USA

    Khaled A. Kamel

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Das, S., Singha, B., Tonda, A., Biswas, A. (2023). Direct Comparative Analysis of Nature-Inspired Optimization Algorithms on Community Detection Problem in Social Networks. In: Shakya, S., Papakostas, G., Kamel, K.A. (eds) Mobile Computing and Sustainable Informatics. Lecture Notes on Data Engineering and Communications Technologies, vol 166. Springer, Singapore. https://doi.org/10.1007/978-981-99-0835-6_45

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