Community Detection in Multidimensional and Multilayer Networks

Abstract

The use of social networking platforms has seen rapid growth recently. People connect to each other using varied platforms but their actions differ with respect to the platforms. This results in heterogeneous relations such as functional relations, spatial relations, and temporal relations. In order to look the interactions from different perspectives and ensemble people with similar activities, an extensive study on community detection in heterogeneous networks is highly recommendable. Particularly, recent research activities have gained a lot of attention for community detection in multidimensional networks and multilayer networks. To this end, we open on various important features of these heterogeneous networks considering their role in the community detection process. Successively, we reviewed several current strategies to further process the earlier heterogeneous community detection approaches based on these features followed by some of the evaluation strategies. Our study aims to guide our attention toward the numerous approaches to detect shared and unshared communities across multiple graph layers, the challenges to the previous approaches, and the developments in the recent approaches.