Abstract
In social networks, Micro Blog has become the most widely used social networking platform. Mining valuable customers is particularly important in the large-scale micro-blog user group, and the influence of the user become the main measure to estimate the user's value. Based on the similarity of micro-blog user groups and Internet node characteristics in structure, this paper proposed an improved PageRank algorithm by user forwarding rate and activity degree estimate the user's influence. Experiment results show that the improved algorithm has good convergence and the influence of the micro blog users can estimate effectively and objectively.
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