Abstract: Through analyzing the characteristics of the cobweb state microblog network, the paper points out the importance of identifying the influential user in the cobweb state micro-blog network. It focuses on the effect of the attributes of micro-blog users itself, combines the principle of PageRank algorithm, and then proposes IUDA(Influential User Discovering Algorithm) in cobweb state micro-blog relationship network to find influential users. Finally, experiments are conducted with the real user data from Sina micro-blog based on this method and are compared with two other methods. The results show that the IUDA method combined with the user itself can find influential users in cobweb state micro-blog network more effectively, and can objectively reflect the user′s influence.

Key words: influential users, micro-blog, micro-blog relationships network, PageRank, centrality analysis