Research on Opinion Diffusion and Evolution Model in Complex Network

The openness and freedom of the Internet have made more and more users choose to spread information on the Internet, which has also led to a sharp increase in the speed and breadth of event information diffusion, and the changes in public opinion have also become more diverse. Motivated by this observation, in this article, we propose an opinion information diffusion model based on opinion dynamics. Through the analysis of the model, the influence of the activation probability and the diffusion willingness in the model on the diffusion result is studied. In addition, we improved the opinion evolution rules in the bounded trust model and analyzed the evolution of group opinions from the perspectives of group size, trust threshold, and acceptance of individual opinions. Finally, based on the idea of reverse influence sampling, positive information propagation maximization (PIPM), a positive information propagation maximization algorithm is proposed, and it is shown by the experimental results that it can effectively solve the problem of maximizing the spread of positive public opinion information. These findings shed new light on the practical application value for controlling the development of public opinion and maximizing the transmission of positive information.