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.