Thorough Examination of Function-Based Community Detection via Social Media for Single and Multiple Purposes (International Journal of Food and Nutritional Sciences, 2022)
As the Internet has grown, social networks have drawn interest as research subjects from a wide range of academic fields. The most precise systems are represented in intricate networks. Complex networks are most commonly characterized by their community structure, in which the relationships between node groups are more intimately linked to one another than with the network as a whole.Finding the main clusters and community structures in complex networks, like web charts and biological networks, enables the discovery of organizational rules. The communities appear to overlap in general. One of the defining characteristics of social networks is overlap, which is the state of an individual being a member of multiple social groups. Overlapping community discovery has drawn a lot of interest recently in social network application domains.Numerous approaches utilizing various tools and techniques have been put forth to address the issue of overlapping community discovery.This paper presents a thorough analysis of single and multi-purpose functions for community detection, as well as a comparative analysis of the heuristic overlap community detection algorithm over social media.