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Community Detection in Social Networks: Literature Review

Author

Listed:
  • Seema Rani

    (Department of Computer Science, Jamia Millia Islamia, New Delhi, India)

  • Monica Mehrotra

    (Department of Computer Science, Jamia Millia Islamia, New Delhi, India)

Abstract

Due to easy and cost-effective ways, communication has amplified many folds among humans across the globe irrespective of time and geographic location. This has led to the construction of an enormous and a wide variety of social networks that is a network of social interactions or personal relations. Social network analysis (SNA) is the inspection of social networks in order to understand the participant’s arrangement and behaviour. Discovering communities from the social network has become one of the key research areas in SNA. Communities discovered from social networks facilitate its members so as to interact with relatable people who have similar or comparable interests. However, in present time, the enormous growth of social networks demands an intensive investigation of recent work carried out for identifying community division in social networks. This paper is an attempt to enlighten the ongoing developments in the domain of Community detection (CD) for SNA. Additionally, it sheds light on the algorithms which use meta-heuristic optimisation techniques to hit upon the community structure in social networks. Further, this paper gives a comparison of proposed methods in recent years and most frequently used optimisation approaches in the domain of CD. It also describes some application areas where CD methods have been used. This guides and encourages researchers to probe and take ahead the work in the area of detecting communities from social networks.

Suggested Citation

  • Seema Rani & Monica Mehrotra, 2019. "Community Detection in Social Networks: Literature Review," Journal of Information & Knowledge Management (JIKM), World Scientific Publishing Co. Pte. Ltd., vol. 18(02), pages 1-28, June.
    • Handle: RePEc:wsi:jikmxx:v:18:y:2019:i:02:n:s0219649219500199
    DOI: 10.1142/S0219649219500199
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    References listed on IDEAS

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    1. Di Jin & Dayou Liu & Bo Yang & Jie Liu & Dongxiao He, 2011. "Ant Colony Optimization With A New Random Walk Model For Community Detection In Complex Networks," Advances in Complex Systems (ACS), World Scientific Publishing Co. Pte. Ltd., vol. 14(05), pages 795-815.
    2. Lü, Linyuan & Zhou, Tao, 2011. "Link prediction in complex networks: A survey," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 390(6), pages 1150-1170.
    3. Gómez, Daniel & Figueira, José Rui & Eusébio, Augusto, 2013. "Modeling centrality measures in social network analysis using bi-criteria network flow optimization problems," European Journal of Operational Research, Elsevier, vol. 226(2), pages 354-365.
    4. Jin, Hong & Wang, Shuliang & Li, Chenyang, 2013. "Community detection in complex networks by density-based clustering," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 392(19), pages 4606-4618.
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