With the popularization and development of the Internet, microblogs have become a mainstream social network platform. The evaluation of user influence has become a research hotspot. Most of the existing researches calculate influence by improving PageRank. But these researches ignored the relationship between users’ interest theme similarity and information dissemination, and didn’t have enough analysis about the interaction behaviors among users. Aiming at these problems, we proposed a new microblog user influence algorithm—MUI-ISIDA (microblog user influence based on interest similarity and information dissemination ability) in this paper, which takes into account users’ interest theme similarity and information dissemination ability. We verified the effectiveness of the proposed algorithm on Sina microblog dataset. The experimental results show that compared with PageRank and MR-UIRank, the proposed algorithm has achieved higher accuracy in user influence ranking.
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