网络与信息安全学报 ›› 2017, Vol. 3 ›› Issue (8): 68-76.doi: 10.11959/j.issn.2096-109x.2017.00190

• 学术论文 • 上一篇    

Information tracing model based on PageRank

LI Qian1,2(),LAI Jia-wei2,XIAO Yun-peng2,WU Bin1   

  1. 1 Beijing Key Laboratory of Intelligent Telecommunications Software and Multimedia,Beijing University of Posts and Telecommunications,Beijing 100876,China
    2 Chongqing Engineering Laboratory of Network and Information Security,Chongqing University of Posts and Telecommunications,Chongqing 400065,China
  • 修回日期:2017-07-05 出版日期:2017-08-01 发布日期:2017-12-26
  • 作者简介:LI Qian (1980-),born in Chongqing. She is working on her Ph.D. degree at Beijing university of posts and telecommunications. Her research interests include social network analysis and information dissemination dynamics.|LAI Jiawei (1992-),born in Jiangxi. She is working on her master degree at Chongqing university of posts and telecommunications. Her research interests include social network analysis and machine learning.|XIAO Yunpeng (1979-),born in Anhui. He received his Ph.D degree of computer science from Beijing university of posts and telecommunications. He is an associate professor in Chongqing university of posts and telecommunications. His research interests include social network analysis and machine learning.|Wu Bin (1969-),born in Hunan. He received his Ph.D degree of institute of computing Chinese academy of sciences in 2002. He is a professor in Beijing university of posts and telecommunications. His research interests include complex network,data mining,massive data parallel processing,visual analysis and telecom customer relationship management.
  • 基金资助:
    National Key Basic Research Program (973 program) of China(2013CB329606);Chongqing Science and Technology Commission Project(cstc2017jcyjAX0099);Science and Technology Research Program of the Chongqing Municipal Education Committee(KJ1500425);Ministry of Education of China and China Mobile Research Fund(MCM20130351)

Qian LI1,2(),Jia-wei LAI2,Yun-peng XIAO2,Bin WU1   

  • Revised:2017-07-05 Online:2017-08-01 Published:2017-12-26

关键词: social network, hot topic, information tracing, PageRank

Abstract:

In social network,original publisher and important nodes in the diffusion process can be traced by analyzing the spreading network of a hot topic.The participated users and spreading network structure of a hot topic build an information tracing model,which mines the source and important diffusion nodes.Firstly,it analyzed the development trend of a hot topic and extracts the users involved.Secondly,it established a user network according to the following relationship of the users involved.Thirdly,the contribution rate of users on the development of the hot topic was initialized,and the PageRank algorithm was used to construct the information tracing model.Finally,the Top k users were selected as the information publisher and important users of the hot topic according to the contribution rate.Experimental results showed that our model can effectively discover the hot topic of the publisher and important users.

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