A Hierarchical Participant Classification Model of Hot Events in Chinese Microblog

Microblog is the most prevalent social platform recently in China, where participants' classification plays a significant role. The existing methods usually categorize the users into limited levels and ignore the hierarchical characteristic of information spread. In this paper, we propose a hierarchical participant classification model based on core group mining and opinion leader identification, and develop an allocation algorithm to calculate the allocated value for comprehensive indices of each user. According to the directions of information dissemination, participants are classified flexibly in terms of their variable information propagation capability. Numerical experiments performed by using the actual data are provided to show the efficiency and feasibility of our model.