Advancements in Community Detection and Analysis Methods: A Comprehensive Review of Networks of Overlapable Communities

Abstract

Community detection is a fundamental problem in complex network analysis, aiming to uncover cohesive groups of nodes with dense internal connections and sparse connections to nodes outside the group. While traditional community detection methods focus on identifying disjoint communities, many real-world networks exhibit overlapping community structures, where nodes can belong to multiple communities simultaneously. Overlapping communities are prevalent in diverse systems, such as social networks, biological networks, and technological networks, where entities often participate in multiple contexts or functionalities.