Study on Relation between Social Circles and Communities in Facebook Ego Networks

Abstract

Community detection is a core problem in social network analysis. Strictly speaking, however, the communities does not exactly correspond to the real group, well-known as social circles. In this paper, we study on 1) how close relation between the ground-truth social circles and communities exists and 2) whether the social circles can be detected by the classical community detection algorithm or not. We use the SNAP facebook dataset to reveal the correlation between the social circles and the detected communities. We listed up the community’s modularity values and the balanced accuracy values with the ground-truth circles per each level in the iterative process of divisive clustering. We analyzed the Spearman’s rank correlation between the paired data. The experimental results show that there is a strong correlation between the ground-truth social circles and the communities detected by classical method.