Dynamic modeling and simulation of double-rumor spreaders in online social networks with IS2TR model

Rumors can spread quickly and widely, causing negative impacts on both society and individuals. Therefore, it is essential to prevent the propagation of rumors to maintain social stability and avoid potential harm to people’s lives. In order to accurately simulate the rumor spreading process, a new IS2TR rumor spreading model is proposed. The different psychology of people when rumor spreading is taken into account in this model, and rumor spreaders are classified as normal spreaders and malicious spreaders. In addition, this model adds truth spreaders, making it more consistent with the real rumor spreading process. First, we calculate the model’s equilibria and the basic reproduction number. Second, the local asymptotic stability and transcritical bifurcation of the equilibria are analyzed and proved in this model. Finally, the theoretical results are verified by numerical simulations, and we also analyze the comprehensive impact of adding malicious spreaders and truth spreaders to the model. A real dataset is then used to predict the rumor propagation process, and the final R-squared is 0.9487 which verifies the effectiveness in predicting rumor propagation trends.