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The literature on opinion dynamics lacks consideration of the changing states of nodes during the process of opinion interaction, as observed in the literature on social networks. To address this gap, this paper proposes an adapted three-dimensional Deffuant–Weisbuch model based on the Susceptible Infected Recovered (SIR) model, which explores the impact of node state changes on opinion interaction. We incorporate the SIR model to describe changes in node state and improve the trust threshold by taking into account nodes' emotional factor, cognitive ability, and state of the arts. The model is also modified using the opinion natural evolution coefficient and accounts for dynamic changes in social network structure. We validate our model with different network types and structures, and verify our results using the Louvain algorithm and index of centrality. Our model reveals that under different network types and structures, multiple opinion cliques are formed, and the opinions of ordinary nodes tend to converge around those of opinion leaders, indicating the guiding role of opinion leaders in shaping public opinion. [Display omitted] • 3-dimension DW model integrates SIR to nodes-changing states on opinion interaction. • Offering a more realistic representation of opinion dynamics in social networks. • Trust threshold for nuanced understanding emotional factors, cognitive abilities. [ABSTRACT FROM AUTHOR]

• A feedback-driven model of message propagation based on the classical SIR model is proposed. • The feedback mechanism affects the structure of the social network, making the network nodes more closely connected. • The level of trust between strangers is one of the most important factors affecting the spread of messages. This paper focuses on the role of feedback mechanism on message propagation. In this paper, we study the effect of feedback on message propagation in terms of both the motivation of the communicator to propagate the message and the trust of the message recipient in the communicator, and we design a decay mechanism of motivation based on Newton's cooling law. Based on these considerations, we propose a model of message propagation based on the feedback mechanism. We verify the effect of feedback on message propagation by performing numerical simulations in the Watts-Strogatz (WS) and Barabasi-Albert (BA) networks. The simulation results show that the feedback mechanism leads to faster and more persistent message propagation and that the degree of influence on message propagation varies across different network structures. The simulation also results show that the feedback mechanism changes the structure of the social network and makes the nodes between the networks more closely connected. [ABSTRACT FROM AUTHOR]