Modelling network public opinion polarization based on SIR model considering dynamic network structure

Abstract

Under the dispute between China and the United States, the international field of public opinion is dominated by increasing tensions, and the network rumors triggered by the COVID-19 epidemic are intensifying. In view of the above-mentioned context, this paper focuses on the development and the evolution process of public opinions. Since the evolution of public opinion is often accompanied by the spread and diffusion of information, this paper combines the process of information diffusion with the development process of polarization behavior, and brings in the dynamic network and the timeliness factor of public opinion dissemination, so as to better explore the polarization process of public opinion under the dynamic network. Then, this paper focuses on the analysis of the parameters of the model and through the dynamic adjustment of parameters, finding out the main factors that affect the trend and development of network public opinion. In addition, this paper introduces an actual case, and takes the actual case data as the support to demonstrate the reliability and practical application value of the model. Finally, based on the simulation results and analysis of actual cases, this paper puts forward the corresponding preventive measures to alleviate the polarization behavior of the group.