热点事件的发生往往会引起网络谣言的肆意扩散。为避免煽动公众情绪、激化社会矛盾, 政府部门需要在网络谣言危机暴发前进行及时且精准的态势研判与应对效率分析。该文开展了网络谣言危机触发机制与拥塞效应分析研究。在分析网络谣言演化体系的基础上, 构建了基于改进传染病传播机理-预警研判模型(SE (ER) IR-SPN)的网络谣言危机触发机制与拥塞效应分析模型; 通过细化潜伏者人群构建SE (ER) IR-SPN触发机制模型, 通过传播平衡点、触发阈值及不同特征人群比例变化趋势获取平衡系统状态和更精确的触发时间, 并通过库所繁忙率和变迁利用率分析进行谣言暴发后危机事件应急处理的流程拥塞效应分析; 以A市某医疗卫生谣言事件为例进行模型适用性验证。研究结果表明：SE (ER) IR-SPN模型可更早发现高危网络谣言事件, 并根据处置流程中库所繁忙率与变迁利用率为政府部门提供应急处置阶段的决策支持。

Objective: Hot events often lead to rampant online rumor spread. To prevent the incitement of public sentiment and the exacerbation of social contradictions, government departments must conduct timely and accurate situation assessment and response efficiency analysis before the outbreak of an online rumor crisis. In this regard, this paper investigates the trigger mechanism and congestion effects of online rumor crises. Methods: By analyzing the evolution system of online rumors, a model for the trigger mechanism and congestion effects of online rumor crises is constructed using the improved susceptible exposed infectious recovered (SEIR) model and the stochastic Petri net (SPN). The constructed trigger model, SE(ER)IR-SPN, is refined by delineating the involved latent population group into exaggerators or rational spreaders. The equilibrium system state and precise trigger timing are obtained by analyzing transmission equilibrium points, trigger thresholds, and the density change trends of different characteristic groups. The congestion effects of emergency responses to crisis events after the outbreak of rumors are analyzed based on the busy rates of places and the utilization rates of transitions. Finally, the model applicability is verified using a medical and health event in City A as a case study. Results: The research indicates that the SE(ER)IR-SPN model can detect high-risk online rumor events early, providing decision support for government departments during the disposal phase based on the busy rates of places and the utilization rates of transitions. The model effectively captures the dynamics of rumor spread and the subsequent congestion effects in emergency response processes. Conclusions: The SE(ER)IR-SPN model is a valuable tool for the early identification of online rumor crises, enabling government departments to make informed decisions during the disposal phase. Detailed analysis of the model components, including the busy rates of places and the utilization rates of transitions, offers insights into the optimization of emergency response workflows. The case study considered herein confirms the practical utility of the model, highlighting the potential for broad application in managing and mitigating the impact of online rumor crises.irms the practical utility of the model, highlighting the potential for broad application in managing and mitigating the impact of online rumor crises.