A Comprehensive Analysis of Dis-Joint Community Detection Algorithms for Massive Datasets - Sutaira, Kamal; Wandra, Kalpesh; Bhensdadia, CK (International Journal of Computer Sciences and Engineering, 2025)
With the growth of Internet and computer knowledge, more and more persons connect socially. People communicate with each other and express their views on social media, which may form a complex network of association. Entities in the social networks create a “relation structure” through several connections which produces a huge amount of information. This “relation structure” is the group or community that we are interested in research. Community detection is very imperative to disclose the structure of social networks, dig to people's views, analyze the information dissemination and grasp as well as control the public sentiment. In recent years, with community detection becoming an essential field of social networks analysis, a large number of the academic literature suggested several approaches to community detection. In this paper, we first describe the concepts of the social network, community, community detection and criterions of community quality. Then we classify the methods of community detection into the following categories. And at last, we summarize and discuss these methods as well as the potential future directions of community detection.