Improved Short-video User Impact Assessment Method Based on PageRank Algorithm

The short-video platform is a social network where users’ content accelerates the speed of information dissemination. Hence, it necessary to identify important users effectively obtain information. Four algorithms (Followers Rank, Average Forwarding, K Coverage, and Expert Survey Evaluation) have been proposed calculate influence determine their importance. These methods simply take number user’s fans or posts as standard evaluation, ignoring factors such paid posters, which makes evaluations inaccurate. To solve these problems, we propose user rank (SVUIR) algorithm, combines direct indirect comprehensively measure users, using reference fans, likes, works, work quality, focus on behavior, comments, forwarding behavior. An experiment verifies algorithm Douyin (i.e., TikTok), typical platform, confirms that SVUIR more comprehensive objective than above four algorithms.