A Class of Public Opinion Dissemination Model considering the Information Screening Mechanism

Suyalatu Dong,Joni Zhong

doi:10.1155/2021/6342976

Abstract

This paper introduces an information screening mechanism based on the general SEIR model of public opinion dissemination in complex networks. Specifically, networks users screen the information disseminated in complex networks based on their knowledge reserve, life experience, and personal preferences. This screening mechanism filters the public opinion disseminated. Based on the quantitative analysis of this mechanism, we establish a new SEIR model of public opinion dissemination in complex networks. The simulation results on the Facebook network data set provide theoretical guidance for the formulation of effective public opinion suppression strategies.

Highlights

With the rapid development of online social networks, the Internet has become more and more embedded in all aspects of people’s lives. e development of computer technology has enabled proliferation of the social networks
In the study of many public opinion dissemination models, researchers often assume that the healthy nodes are like a blank sheet of paper
In such models’ healthy nodes when facing the public opinion, they have no preference and judgment ability; . they join in the process of public opinion dissemination unconditionally

Summary

Introduction

With the rapid development of online social networks, the Internet has become more and more embedded in all aspects of people’s lives. e development of computer technology has enabled proliferation of the social networks. It can be seen that the first group of coefficients ε and ξ proposed in this paper are similar to the quantitative description of social reinforcement mechanism, information receiving probability λ, discussed in reference [27]. With the increase of users with less knowledge reserve, less scientific literacy and less profound life accumulation, individual users will be affected to make positive reactions to negative public opinion (that is, praise, comment, or forward the information). E second group of coefficients σ proposed in this paper for public opinion screening mechanism are exactly the same as that of information receiving probability λ, which is the quantitative description of social strong social reinforcement mechanism discussed in reference [27], because in the process of proposing σ, memory and cumulative effects of public opinion dissemination are considered. We analyze the numerical simulation results of the discrete SEIR model (3); in the fourth part, we analyze the simulation results of the continuous SEIR model (1) and compare the two models

Numerical Simulations of the Discrete SEIR Model

Simulation Experiment of the Continuous SEIR Model

Findings

Conclusions