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Social Media Retrieval pp 65–85Cite as

Survey on Social Community Detection

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Part of the book series: Computer Communications and Networks ((CCN))

Abstract

Community detection is a growing field of interest in the area of social network applications. Many community detection methods and surveys have been introduced in recent years, with each such method being classified according to its algorithm type. This chapter presents an original survey on this topic, featuring a new approach based on both semantics and type of output. Semantics opens up new perspectives and allows interpreting high-order social relations. A special focus is also given to community evaluation since this step becomes important in social data mining.

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Authors and Affiliations

  1. Laboratoire de Genie Informatique et d’Ingenierie de Production (LGI2P), EMA - Ecole des Mines, Site EERIE, Parc Scientifique Georges Besse, F-30035, Nîmes cedex 1, France

    Michel Plantié & Michel Crampes

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  1. Michel Plantié
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  2. Michel Crampes
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Correspondence to Michel Plantié .

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Editors and Affiliations

  1. Department of Electronic Engineering, Queen Mary University of London, Mile End Road, London, E1 4NS, United Kingdom

    Naeem Ramzan

  2. Director of Product Innovation, Search, Netflix, Winchester Circle 100, Los Gatos, 95032, California, USA

    Roelof van Zwol

  3. School of Integrated Technology, Yonsei University, 162-1 Songdo-dong, Yeonsu-gu, Incheon, 406-840, Korea, Republic of (South Korea)

    Jong-Seok Lee

  4. Institut für Telekommunikationssysteme, Technische Universität Berlin, Einsteinufer 17, Berlin, 10587, Germany

    Kai Clüver

  5. Media Computing Group, Microsoft Research, 555 108th Ave NE, Bellevue, 98004, Washington, USA

    Xian-Sheng Hua

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Plantié, M., Crampes, M. (2013). Survey on Social Community Detection. In: Ramzan, N., van Zwol, R., Lee, JS., Clüver, K., Hua, XS. (eds) Social Media Retrieval. Computer Communications and Networks. Springer, London. https://doi.org/10.1007/978-1-4471-4555-4_4

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  • DOI: https://doi.org/10.1007/978-1-4471-4555-4_4

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