Two-Layer Coupled Network Model for Topic Derivation in Public Opinion Propagation

作     者：Yuexia Zhang Yixuan Feng Yuexia Zhang;Yixuan Feng

作者机构：School of Information and Communication EngineeringBeijing Information Science&Technology UniversityBeijing 100101China 

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

年 卷 期：2020年第17卷第3期

页      面：176-187页

核心收录：

学科分类：050302[文学-传播学] 05[文学] 07[理学] 070104[理学-应用数学] 0503[文学-新闻传播学] 0701[理学-数学] 

基　　金：in part by the National Natural Science Foundation of China(No.51334003) 

主　　题：complex network public opinion propagation SEIR model 

摘      要：In view of the fact that news can generate derivative topics when it spreads through micro-blogs,a two-layer coupled SEIR public opinion propagation model is proposed in this *** model divides the process of public opinion propagation into two layers:the original topic layer and the derived topic *** are transmitted separately by the SEIR model in the two topic layers,which are independent and *** influence of the topic derivation rate on the propagation trend is established by solving for the equilibrium point and propagation ***,we establish the relationship between the original topic and the derived topic by *** paper uses the Baidu index to demonstrate the correctness of the *** relationship between the derived topic and the original topic is verified by adjusting the parameters by the control variable *** results show that the proposed model is consistent with the propagation of actual public opinion.