Abstract: In order to identify the key figures in social networks,we need to assess the user influence.Influence is gra-dually formed on the base of the information propagation.This paper built a model to describe the process of influence propagation.Then,based on the model,we used label to indicate the original owner of influence and used degree of membership to indicate the effect degree of which users are affected.We utilized multi-label propagation to simulate the process of users’ influence propagation to achieve a new user influence assessment algorithm MLPIA (Multi-label Propagation User Influence Assessment Algorithm).Lastly,the coverage area and closeness centrality of top users’ influence were tested on real data set.The results demonstrate the rationality and validity of the proposed algorithm.

Key words: User influence,Multi-label propagation,Influence propagation,Social networks,Effect judgment