Abstract
As a convenient and popular social network platform, microblogging has become an important medium for people’s information exchange. The development of microblogging network can be regarded as a growth of complex network, and dissemination of information in microblogging network shows strong regularity. In the face of big scale of users, the appraisal of user influence become an important index to measures the value of a user. How to recognize user influence becomes a hot topic in microblogging research. In this paper, we proposed a method named InformationRank to evaluate user influence, which based on measure the information of node betweenness centrality in the network. Then, we analyze and compare the efficiency of this method with PageRank algorithm and Hits algorithm. The experimental results indicate that InformationRank algorithm is effective in a large scale network.
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