To solve the less comprehensive and objective problem of the traditional microblog user influence evaluation algorithms, through the analysis of the definition and influencing factors of microblog user influence, this paper proposes an improved user influence ranking algorithm based on PageRank algorithm, named as Self and Followers User Influence Rank (SF-UIR). The user's own factors are quantified by using the three indicators, the number of followers, the situation of certification, and the microblog dissemination ability, and the poor objectivity situation of PageRank values for user influence ranking is improved. The disadvantage of influence equivalent transfer of the followers' influence is overcame by adopting weighting factor to distribute the influence contribution value of different followers scientifically and quantitatively. Compared with the four mainstream algorithms, the results show that the proposed algorithm is more comprehensive, more objective, and can reflect the influence of microblog users better because of considering the influencing factors based on the user's behavior and followers factors based on the topology, which can effectively solve the interference problem of "zombie fan" in a number of followers ranking algorithm. It can reflect the user's influence level more realistically than average forwarding number algorithm, and can availably avoid the serious defects of not taking the microblog user's behavior into account and giving equal treatment to all followers in K-coverage algorithm. The proposed algorithm can greatly improve the shortage of relying solely on the quantity and quality of followers in PageRank algorithm.