Fractional STIR Epidemic Model for Opinion Dissemination in Social Networks

Social networking services (SNS) have become the main channels for public opinion due to their large users, highly connected interactivity and the immediacy of dissemination. Therefore, it is of great theoretical and practical significance to study the transmission mechanism of Internet public opinion and master the law of public opinion transmission. Based on the traditional SIR epidemic model, this paper introduces Thoughtful (T), a new node that receives transmitted information but considers whether to spread. It also considers the dynamic process of some immunizers becoming communicators and derivative effects. In this paper, a fractional STIR model is proposed, which is based on conformable derivatives and the STIR model. By implementing the MATLAB simulation, the experimental results show that the fractional STIR model has a high degree of fit of the actual data with a small error. Therefore, our model can effectively describe the dynamic process of the evolution of Internet public opinion.