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Social Network Analysis and Mining

Erschienen in:

01.12.2024 | Review Paper

A comprehensive view of community detection approaches in multilayer social networks

verfasst von: Imen Hamed, Wala Rebhi, Narjes Bellamine Ben Saoud

Erschienen in: Social Network Analysis and Mining | Ausgabe 1/2024

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Abstract

Multilayer social networks are the main representative form for today’s social networks. In fact, the multiplicity of relations, the huge amount of data and the dynamic nature of nowadays social networks impose the representation of the network with multiple layers. This new representation makes network analysis more challenging especially Community retrieval. So, researchers propose different approaches to handle these challenges to detect accurate communities in the multilayer networks. The main goal of this paper is to present a novel and comprehensive view on community detection strategies within multilayer social networks. To do so, we provide a taxonomy of existing methods in static and dynamic multilayer social networks. Additionally, we introduce a "four worlds framework" to offer a comprehensive comparison of the different existing community detection methods. Lastly, we outline potential avenues for future research and highlight some unresolved challenges in this domain.

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Titel: A comprehensive view of community detection approaches in multilayer social networks
verfasst von: Imen Hamed
Wala Rebhi
Narjes Bellamine Ben Saoud
Publikationsdatum: 01.12.2024
Verlag: Springer Vienna
Erschienen in: Social Network Analysis and Mining / Ausgabe 1/2024
Print ISSN: 1869-5450
Elektronische ISSN: 1869-5469
DOI: https://doi.org/10.1007/s13278-024-01266-1

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