Super User Influence Detection Algorithm in Microblog Networks

In a Microblog (i.e., Weibo) network, there are special users who induce other users to actively utilize microblogs. Identifying such influential users is important when establishing business strategy and models for the Microblog network. In this paper we focus on the research of the Sina Micro-blog. First of all, we tried using a new way to define the super users whose micro-blogs exhibit significant influences over other users. The new definition can classify or cluster these super users in a different perspective. Second, we constructed a model based on the dissemination of micro-blogs and the actions of users; this model can explain the diffusion of micro-blogs' influence and can successfully describe the impact of the propagation and dissemination of the information in the Micro-blog network. Third, we proposed a method of identifying the super users, called User Influence Detection Algorithm Based on Micro-blog's Spreading Cascade, referred to as UISC Algorithm. What's more, we analyzed the performance of the proposed method by applying it to an actual Micro-blog network and the experimental results show that the UISC outperforms other methods we compared.