Communities' Detection in Social Networks: State of the art and perspectives

Abstract

Nowadays, social networks have been widely used by different people for different purposes in the world. The discovering of communities and clustering is a widespread subject in the space of social networks analysis. Many interesting solutions have been proposed in the literature, such as the algorithms of Newman and Girvan. However, most solutions have common problems: the stability and the community structures quality. In this paper, we give a state of the art, from 1970 until 2018 on the approaches as well as the algorithms of communities' detection in social networks. This study aims to gives a comparison between the different proposed architectures;