User Influence in Microblog Based on Interest Graph.

Microblog is currently the largest social networking platform in China. In recent years, as a social media, the infiuence of microblog continues to expand. The users who have large infiuence play a guiding role in the spread of microblog, and even guide the trends of public opinion. Therefore, we propose an infiuence analysis method to find microblog users who are with great infiuence, which is of great significance for the research and mining of microblog. User infiuence analysis in microblog has great difficulties due to the limited amount of microblog information, quick updates and nonstandard microblog language. First, we use the label propagation algorithm combined with LDA algorithm to divide users by the user interest graph, according to the social relationship of microblog users and the content they generate. Then, depending on different interest areas, an improved PageRank algorithm based on user interaction behavior is proposed to calculate the user's infiuence. Experiments on the real datasets show that the proposed method outperforms the traditional algorithms. [ABSTRACT FROM AUTHOR]