Empirical studies on the network of social groups: the case of Tencent QQ

TL;DR

This paper analyzes Tencent QQ's online social network data to uncover social interaction patterns, group growth, and demographic influences, providing insights difficult to obtain from traditional social studies.

Contribution

It introduces a comprehensive analysis of Tencent QQ's social group networks, revealing new behavioral patterns and relationships at microscopic and mesoscopic levels.

Findings

Insights into group growth dynamics

Interactions between groups and members

Relationships between demographics and social behaviors

Abstract

Participation in social groups are important but the collective behaviors of human as a group are difficult to analyze due to the difficulties to quantify ordinary social relation, group membership, and to collect a comprehensive dataset. Such difficulties can be circumvented by analyzing online social networks. In this paper, we analyze a comprehensive dataset obtained from Tencent QQ, an instant messenger with the highest market share in China. Specifically, we analyze three derivative networks involving groups and their members -- the hypergraph of groups, the network of groups and the user network -- to reveal social interactions at microscopic and mesoscopic level. Our results uncover interesting behaviors on the growth of user groups, the interactions between groups, and their relationship with member age and gender. These findings lead to insights which are difficult to obtain in ordinary social networks.