This paper takes the emotional information dissemination network of users on the converged media platform in the English context as the research object, constructs an adaptive dissemination model integrating emotional factors, and combines empirical analysis to reveal the dynamic laws of emotional dissemination. Based on the theory of emotion generation, the behavioral mechanism of users from event cognition to emotional expression is studied and proposed. The Survival Analysis Model (SAM) is introduced to quantify the probability of emotion cascade dissemination in continuous time. The user interaction process is dynamically characterized through the risk function and survival function, and the “seeking common ground” and “preserving differences” dual models and the Big Five personality theory are integrated to construct the user paranoia model. To analyze the heterogeneity of forwarding behavior. The empirical part selected the environmental protests in the UK in 2023, collected 58,329 valid comment data from the Twitter platform, and conducted research by combining sentiment tendency analysis, network centrality measurement and time series tracking. The results show that the user emotional tendency (Q=±0.988 to -0.998) shows a significant polarization. Gender r=0.123, the number of followers r=0.085 and tag usage r=0.227 are significantly positively correlated with positive emotions, while age r=-0.058 and the number of comments and likes r=-0.135 are associated with negative emotions. The analysis of network centrality indicates that core nodes such as the point degree centrality of @JustStop_Oil at 5.55 and the intermediary centrality of @BillMcKibben at 176 dominate the dissemination of public opinion. The frequency distribution of emotion words conforms to the power-law feature. The high-frequency word “Disrespectful” appears 45,286 times. Negative emotions account for 81.08% and dominate the entire event, while positive and neutral emotions have a short peak at the beginning and then gradually fade away. The “angrier driven communication” effect is significant in controversial events, and the model can provide theoretical and empirical support for the emotional communication mechanism and public opinion management of social media.
