Research on User Influence in Microblog Based on Interest Graph

Microblog1 is currently China's largest social networking platform. In recent years, as a social media, microblog influence continues to expand. The users who have large influence play a guiding role in the spread of microblog, and even lead to public opinion tendency. Therefore, we can use the method of influence analysis to find microblog users who are with great influence, which is of great significance for the research and mining of microblog. User influence analysis in microblog has great difficulties due to the short microblog information, update quickly and nonstandard microblog language. Firstly, according to the social relationship of microblog users and the microblog content that users generate, we use label propagation algorithm combined with LDA (Latent Dirichlet Allocation) algorithm to divide users by user interest graph. Then, on the basis of different interest areas, an improved PageRank algorithm based on user interaction behavior is proposed to calculate the user's influence. Finally, the experimental results are analyzed and compared. The results showed that the proposed method can obtain better results.