[目的/意义]设计针对性的场景治理策略回应复杂治理需求，提高深度伪造事件舆情信息治理的精细化和场景化水平，突破现有治理策略纵向深度和适配精度的应用局限性。[方法/过程]融合风险管理理论和场景理论，以深度伪造事件舆情信息风险感知为因变量，以伪造技术、公众认知、媒体传播、危害程度、影响范围、应对能力、监管规范为自变量，构建了AIGC时代深度伪造事件舆情信息风险感知的影响因素模型和因果驱动模型。[结果/结论]在个人隐私事件中，各变量均不构成高风险感知的必要条件；得到了16条深度伪造事件舆情信息高风险感知的组态路径，提炼出了风险识别场景、风险评估场景和风险应对场景三种治理模式，并提出了深度伪造事件
舆情信息的场景治理策略。

[Purpose/significance] This article designs targeted scene governance strategies to respond to complex gov⁃ernance needs. It improves the refinement and scenarization level of the governance of deepfake events public opinion information. It breaks through the limitations of the vertical depth and adaptation accuracy of existing governance strate⁃gies. [Method/process] By integrating risk management theory and scenario theory, this article takes the perception of public opinion information risk in deepfake events as the dependent variable, and forgery technology, public aware⁃ness, media dissemination, degree of harm, scope of impact, response capability, and regulatory norms as independent variables. It has constructed a model of influencing factors and causal driving factors for the perception of public opin⁃ion information risk in the AIGC era of deepfake events. [Result/conclusion] In personal privacy events, none of the variables constitute a necessary condition for high-risk perception. This article has obtained 16 configuration paths for
high-risk perception of public opinion information in deepfake events. It has refined three governance models: risk identification scene, risk assessment scene, and risk response scene, and proposed scene governance strategies for deepfake events public opinion information.