Affiliations: [a] College of Computer Science and Engineering, Shandong Province Key laboratory of Wisdom Mine Information Technology, Shandong University of Science and Technology, Qingdao, China
| [b]
Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences, Shenzhen, China
Correspondence:
[*]
Corresponding author. Zhongying Zhao, College of Computer Science and Engineering, Shandong University of Science and Technology, Qingdao 266590, China. Tel.: +86 532 86057524; Fax: +86 532 86057758; E-mail: [email protected].
Abstract: 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.
Keywords: Influential user detection, user behavior analysis, clustering, social
media data mining
