The users’ interactive behaviors of the online group chat and an accurate identification of users’ interaction, which can provide method support for mining user interests and the crowd labeling, was analyzed in this paper. By using social network analysis method, the study took QQ Group “TuanRenTang” as an example to analyze users’ interactive behaviors, discover users’ interaction relationships, construct interaction networks, and explore the interaction types and community detection. The findings suggested that both explicit and implicit interaction exist in the same topic discussion. Users could be classified into four categories: active interaction, general interaction, passive interaction and lurking interaction based on different user activity. Besides, twenty “experts” and eight communities on the basis of interaction networks had been found out from the sample data of “TuanRenTang” chat records.
Zhu, Lei; Xue, Chunxiang; and Wu, Xiuzhi, "Exploring Users’ Interactive Behaviors in Online Group: A Case Study of QQ Group “TuanRenTang”" (2018). WHICEB 2018 Proceedings. 9.