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Online social network analysis: detection of communities of interest

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Abstract

The second generation of World Wide Web, supplied with the platforms of Social Networks, proves to be a revealing source of knowledge. It has led to the emergence of online communities of interest. In fact, the interactions of users through web usages allow the exchange of information and the dissemination of innovation; thereby the formation of cohesive groups of individuals sharing goals, interests, semantics and services. Reflection on the evolution of those groups and their detection is a fundamental topic of interest in the field of Social Network Analysis. This problem is very challenging and hard to solve despite the huge interdisciplinary research over the past years. In this paper, we will attempt an indepth comparative review of the proposed approaches for clustering Social Network actors into communities of interests and propose a new classification of these approaches.

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Authors and Affiliations

  1. Laboratoire d’Automatique, de Mécanique et d’Informatique Industrielles et Humaines, Université de Valenciennes et du Hainaut-Cambrésis (UVHC) Batiment Jonas Le Mont Houy, F59313, Valenciennes CEDEX 9, France

    Nadia Chouchani & Mourad Abed

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  1. Nadia Chouchani
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  2. Mourad Abed
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Correspondence to Nadia Chouchani.

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Chouchani, N., Abed, M. Online social network analysis: detection of communities of interest. J Intell Inf Syst 54, 5–21 (2020). https://doi.org/10.1007/s10844-018-0522-7

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