Social Network Information Propagation Model Based on Individual Behavior

作     者：Lejun Zhang Hongjie Li Chunhui Zhao Xiaoying Lei Lejun Zhang;Hongjie Li;Chunhui Zhao;Xiaoying Lei;College of Information Engineering, Yangzhou University;College of Computer Science and Technology, Harbin Engineering University

作者机构：College of Information Engineering Yangzhou University College of Computer Science and Technology Harbin Engineering University 

出 版 物：《China Communications》 (中国通信（英文版）)

年 卷 期：2017年第14卷第7期

页      面：78-92页

核心收录：

学科分类：050302[文学-传播学] 05[文学] 0503[文学-新闻传播学] 

基　　金：sponsored by the National Natural Science Foundation of China under grant number No. 61100008 the Natural Science Foundation of Heilongjiang Province of China under Grant No. LC2016024 

主　　题：social network information propagation individual behavior propagation delay 

摘      要：In this paper, we discuss building an information dissemination model based on individual behavior. We analyze the individual behavior related to information dissemination and the factors that affect the sharing behavior of individuals, and we define and quantify these factors. We consider these factors as characteristic attributes and use a Bayesian classifier to classify individuals. Considering the forwarding delay characteristics of information dissemination, we present a random time generation method that simulates the delay of information dissemination. Given time and other constraints, a user might not look at all the information that his/her friends published. Therefore, this paper proposes an algorithm to predict information visibility, i.e., it estimates the probability that an individual will see the information. Based on the classification of individual behavior and combined with our random time generation and information visibility prediction method, we propose an information dissemination model based on individual behavior. The model can be used to predict the scale and speed of information propagation. We use data sets from Sina Weibo to validate and analyze the prediction methods of the individual behavior and information dissemination model based on individual behavior. A previously proposedinformation dissemination model provides the foundation for a subsequent study on the evolution of the network and social network analysis. Predicting the scale and speed of information dissemination can also be used for public opinion monitoring.