Opinion dynamics based on infectious disease transmission model in the non-connected context of Pythagorean fuzzy trust relationship

Abstract

In a social network, people may express opinions and interact with others for a hot issue, in which the trust relationship plays an important role. For the determination of the trust relationship, there exists uncertainty, incomplete and non-connected challenges. In this article, we firstly introduce infectious disease transmission model to describe three types of people in a social network. Then, we propose an absorption law and the modified trust propagation and aggregation method to construct a complete connected social network. Furthermore, the improved DEMATEL method is designed to find the most influential people. In the process of opinion evolution, we consider the dynamic change of each people in three types through SIR model. Finally, we use a comprehensive experiment to illustrate our proposed algorithms. The experiment shows that our method can successfully describe the opinion evolution process and presents the flexibility of opinions.