许丹青,刘奕群,张 敏,马少平. 基于在线社会网络的用户影响力研究[J]. 中文信息学报, 2016, 30(2): 83-89.
XU Danqing, LIU Yiqun, ZHAMG Min, MA Shaoping. Study on User Influence in Online Social Networks. , 2016, 30(2): 83-89.
(State Key Lab of Intelligent Technology and Systems, Tsinghua National Laboratory for Information Science and Technology, Department of Computer Science and Technology, Tsinghua University, Beijing 100084, China)
Abstract：Based on the large-scale social network dataset, this paper conducts a multi-feature statistical analysis on graph structure and finds that the indegree, outdegree and posts of social networks generally fit power law distribution. The “small-world” property makes the strongly connected structure of social network show the “spindle” shape. Furthermore, this paper incorporates users posting behaviors, browsing behaviors and social communities properties into social influence modelings. Experimental results show that the PTIM model combining users behaviors and link relationships has a stable performance on identifying the numbers of fans, authenticated users, the relative influence of users pairs and other indices.
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2016, Vol. 30 
