[Purpose/Significance] Online public opinion propagation poses a severe challenge to social stability and even national security. This study aims to establish an online public opinion propagation model that features both mechanistic interpretation and policy evaluation capability, thereby providing decision-making support for online public opinion governance and national security protection. [Method/Process] Based on the basic SEIQR model, this study reconfigured state transition rules and information diffusion patterns to develop an extended SEIQR model that better reflects real-world online public opinion propagation chains. An agent-based modeling (ABM) approach was then employed to reproduce the full-cycle dynamic process of online public opinion propagation at the micro-level of individual interactions. Furthermore, three categories of governance mechanisms—government disclosure of authoritative information, regulatory and platform-imposed account restrictions, and public education and guidance—were systematically simulated, and their intervention effects were comparatively analyzed using quantitative indicators. [Result/Conclusion] The results indicate that, compared with the baseline scenario, the infection peak size decreases sequentially across the “Truth”, “Penalty” and “Education” scenarios; meanwhile, the time at which the infection reaches its peak is progressively delayed, and the number of individuals who never enter the propagation chain sequentially increases. These findings indicate that the above mechanisms can reduce the infection peak, slow down the propagation speed, and narrow the scope of influence to varying degrees by affecting the state-transition process of online users. However, the propagation cycle is extended under all three scenarios, indicating that the propagation chain exhibits a certain degree of a “long-tail effect” under policy interventions. This study identifies the evolutionary patterns of online public opinion under different governance strategies, providing quantitative support for predicting public opinion development trends, optimizing the timing of policy interventions, and scientifically evaluating governance strategies. The findings offer significant theoretical contributions and practical value for fostering a clean and healthy online environment and safeguarding national security and social stability.