High influential users are playing an important role in promoting information propagation in social media. Thus, it has been a very interesting problem to identify influential users in social media, and attracted numerous researchers. A great deal of research work has been devoted to solving this problem. However, the existing methods mainly focus on the network topology, ignoring users’ behaviors. In this paper, we propose an High Influential Users Detection (HIUD) algorithm by analyzing users’ behaviors. To evaluate the performance of our algorithm, we carry out extensive experiments on Sina and Tencent microblogging data sets, and compare it with other methods. The experimental results have shown that the HIUD achieves the best performance. Furthermore, we also make a spatial analysis on those high influential users with thermodynamic map.
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