Information tracing model based on PageRank

作     者：LI Qian LAI Jia-wei XIAO Yun-peng WU Bin LI Qian LAI Jia-wei XIAO Yun-peng WU Bin

作者机构：Beijing Key Laboratory of Intelligent Telecommunications Software and MultimediaBeijing University of Posts and Telecommunications Chongqing Engineering Laboratory of Network and Information SecurityChongqing University of Posts and Telecommunications 

出 版 物：《网络与信息安全学报》 (Chinese Journal of Network and Information Security)

年 卷 期：2017年第3卷第8期

页      面：68-76页

学科分类：12[管理学] 1201[管理学-管理科学与工程(可授管理学、工学学位)] 08[工学] 081201[工学-计算机系统结构] 0812[工学-计算机科学与技术（可授工学、理学学位）] 

基　　金：National Key Basic Research Program(973 program)of China(No.2013CB329606) Chongqing Science and Technology Commission Project(No.cstc2017jcyj AX0099) Science and Technology Research Program of the Chongqing Municipal Education Committee(No.KJ1500425) Ministry of Education of China and China Mobile Research Fund(No.MCM20130351) 

主　　题：计算机网络 网络管理 应用程序 信息安全 

摘      要：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 Page Rank 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.