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Community Structure Detection Using Firefly Algorithm

Author

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  • Ameera Saleh Jaradat

    (Computer Science Department, Yarmouk University, Irbid, Jordan)

  • Safa'a Bani Hamad

    (Yarmouk University, Irbid, Jordan)

Abstract

This article describes how parallel to the continuous growth of the Internet, which allows people to share and collaborate more, social networks have become more attractive as a research topic in many different disciplines. Community structures are established upon interactions between people. Detection of these communities has become a popular topic in computer science. How to detect the communities is of great importance for understanding the organization and function of networks. Community detection is considered a variant of the graph partitioning problem which is NP-hard. In this article, the Firefly algorithm is used as an optimization algorithm to solve the community detection problem by maximizing the modularity measure. Firefly algorithm is a new Nature-inspired heuristic algorithm that proved its good performance in a variety of applications. Experimental results obtained from tests on real-life networks demonstrate that the authors' algorithm successfully detects the community structure.

Suggested Citation

  • Ameera Saleh Jaradat & Safa'a Bani Hamad, 2018. "Community Structure Detection Using Firefly Algorithm," International Journal of Applied Metaheuristic Computing (IJAMC), IGI Global, vol. 9(4), pages 52-70, October.
    • Handle: RePEc:igg:jamc00:v:9:y:2018:i:4:p:52-70
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