A systematic review and bibliometric analysis of community detection methodologies in dynamic networks Online publication date: Sat, 30-Oct-2021
by Namika Makhija; Shashank Mouli Satapathy; Ashish Kumar Dwivedi
International Journal of Business Information Systems (IJBIS), Vol. 38, No. 1, 2021
Abstract: With the growing use of the internet, the number of relationships between individuals has increased in large numbers. This has necessarily paved the way for community detection, which is one of the primary methods to analyse social networks. There have been several methodologies proposed for community detection in the past, which are systematically contrasted against each other in the following sections. The aim of this research article is to analyse the various proposed methods for community detection on six primary basis: most commonly used algorithms, the research interest of the topic, country-based interest, author co-citation network, other investigated domains, and the relationship between citations and year of publications and algorithms. A set of research questions is formulated that addresses the objective of conducting this literature survey. A search strategy is employed to cater to the required set of articles.
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