Calculating influence based on the fusion of interest similarity and information dissemination ability

Authors: SHULIN CHENG, ZIMING WANG, MENG QIAN, SHAN YANG, XIN ZHENG

Abstract: With the popularization, in-depth development and application of the Internet, microblogs have become a mainstream social network platform. Several studies on social networks have conducted researches, and user influence evaluation is an important research hotspot. Most of the existing studies calculate user influence by improving PageRank and have achieved certain results. However, these studies ignored the fusion of users' interest theme similarity and information dissemination ability, and the analysis of interaction behaviors among users is not comprehensive. To address these issues, we propose a new microblog user influence algorithm called microblog user influence based on interest similarity and information dissemination ability (MUI-ISIDA), which fully integrates user's interest theme similarity and information dissemination ability. We construct the model of interest theme similarity and then allocate followers' contributions to the influence of bloggers reasonably. Considering the quality of microblogs, the numbers of forwarding, commenting, and effective interaction behaviors among users, the microblog quality coefficient and the assimilation effect coefficient are designed. On this basis, a user's information dissemination ability model was constructed. We verified the effectiveness of the proposed algorithm using a real dataset. According to these experimental results, our proposed algorithm achieved higher accuracy in ranking user influence than other state-of-the-art algorithms.

Keywords: Microblog, user influence, PageRank, user interest, effective interaction

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