Modeling and Simulation of Network Public Opinion Propagation Model Based on Interest Matching in Social Network

2019 ◽  
pp. 406-418
Author(s):  
Zhang Deliang ◽  
Bin Sheng ◽  
Sun Gengxin
Keyword(s):  
Public Opinion ◽  
Social Network ◽  
Modeling And Simulation ◽  
Propagation Model ◽  
Model Based ◽  
Network Public Opinion

scholarly journals Network public opinion propagation model based on the influence of media and interpersonal communication

2019 ◽  
Vol 33 (32) ◽  
pp. 1950393 ◽  
Author(s):  
Yue-Xia Zhang ◽  
Yi-Xuan Feng ◽  
Rui-Qi Yang
Keyword(s):  
Public Opinion ◽  
Interpersonal Relationships ◽  
Media Coverage ◽  
Rapid Development ◽  
Propagation Model ◽  
Practical Significance ◽  
Seir Model ◽  
Model Based ◽  
The Impact ◽  
Network Public Opinion

With the rapid development of the Internet, social media networks have become the primary platform for people to express their views. In addition, network public opinion has a considerable influence on society. Thus, considering the significant impact of online public opinion on society, it is necessary to study and analyze the propagation process for public opinion. In this study, we propose the Media and Interpersonal Relationship-SEIR (MI-SEIR) model based on the SEIR model. Our proposed model considers the impact of media transmission and interpersonal relationships on opinion propagation. Our MI-SEIR model divides the propagation nodes into three categories: support, neutral and opposition. There is a discussion mechanism between these nodes that represents the node’s viewpoint value evolution rule based on the node firmness, influence of nodes, quality of media coverage and parameters of infection. The state transition of nodes is decided based on the change of opinion value. Our simulation experimental results show that this model is more representative of the real propagation of online public opinion and is thus of practical significance for research and opinion analysis applications.

scholarly journals Poll-Confident Voters in Iterative Voting

2019 ◽  
Vol 33 ◽  
pp. 2205-2212
Author(s):  
Anaëlle Wilczynski
Keyword(s):  
Public Opinion ◽  
Social Network ◽  
Incomplete Information ◽  
Strategic Voting ◽  
Descriptive Model ◽  
Model Based ◽  
The Social ◽  
Public Opinion Polls ◽  
Opinion Polls ◽  
Iterative Voting

This article deals with strategic voting under incomplete information. We propose a descriptive model, inspired by political elections, where the information about the vote intentions of the electorate comes from public opinion polls and a social network, modeled as a graph over the voters. The voters are assumed to be confident in the poll and they update the communicated results with the information they get from their relatives in the social network. We consider an iterative voting model based on this behavior and study the associated “poll-confident” dynamics. In this context, we ask the question of manipulation by the polling institute.

scholarly journals Research on Public Opinion Propagation Model in Social Network Based on Blockchain

2019 ◽  
Vol 60 (3) ◽  
pp. 1015-1027 ◽  
Author(s):  
Gengxin Sun ◽  
Sheng Bin ◽  
Meng Jiang ◽  
Ning Cao ◽  
Zhiyong Zheng ◽  
...  
Keyword(s):  
Public Opinion ◽  
Social Network ◽  
Propagation Model

scholarly journals Analysis and Mining of Internet Public Opinion Based on LDA Subject Classification

2021 ◽  
Author(s):  
Mei Zhang ◽  
Huihui Su ◽  
Jinghua Wen
Keyword(s):  
Public Opinion ◽  
Social Network ◽  
Subject Classification ◽  
Public Opinions ◽  
R Language ◽  
Word Cloud ◽  
Network Public Opinion

This paper uses Python, R language, Gephi and other software to crawl and classify the comment content of Weibo hot search events. Using word cloud, co-occurrence social network graphs, LDA topic classification visualization methods, this paper regularizes and integrates public opinions of hot events. Through this research, we can get the influence of public opinion mediators, public opinion objects, and government forces on the network public opinion and put forward corresponding improvement suggestions. We hope to contribute to the government’s governance and prevention of online public opinion during the spread of COVID-19 and other public hot events.

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