AI谣言次生舆情风险态势感知理论模型构建
Construction of a Theoretical Model for Situation Awareness of Secondary Public Opinion Risks Caused by AI Rumors
摘要
[目的/意义]AI谣言次生與情隐蔽性强、爆发迅猛、传播迭代快，是网络治理中易被忽略的新型隐性治理难题。为优化网络舆情治理架构、缓释社会治理风险，亟需系统梳理其形成机制、演化特征与风险类型，搭建针对性的风险态势感知体系。[方法/过程]立足生成式AI情境的独特性，阐述AI谣言次生舆情的概念、类型与特征。基于信息生态理论提取信息主体、信息本体、信息技术和信息环境4个风险要素，构建数据层、理解层、预警层、决策层的感知框架，整合舆情数据采集、态势评估理解、风险特征提取、与行为决策反馈等核心模块，实现AI谣言次生舆情风险态势感知理论模型构建。[结果/结论]构建了较为完备的AI谣言次生舆情风险态势感知理论模型，丰富了生成式人工智能网络舆情风险治理理论体系。实例分析结果表明，本研究构建的AI谣言次生舆情风险态势感知理论模型具有一定的科学性和适配性，能够为AI谣言次生舆情风险治理提供理论支撑和实践参考。
Abstract
[Purpose/Significance] AI-generated rumors are characterized by low-cost generation, high simulation degree, and cross-platform multi-channel diffusion. Different from traditional network rumors, the secondary public opinion derived from AI rumors has more complex propagation links, faster evolution rhythm, blurred risk spillover boundaries, and overlapping public emotional conflicts, which significantly increases the uncertainty of network public crises and brings new challenges to precise and proactive public opinion governance. In the context of frequent AI false information incidents, traditional single-dimensional monitoring methods are difficult to capture hidden derivative risks. Therefore, constructing a targeted and systematic risk situation awareness model is crucial to realize early warning, dynamic identification and scientific disposal of AI rumor secondary public opinion risks.[Method/Process] This study fully considers the unique risk formation mechanism of public opinion in the generative AI scenario. On the basis of defining the core connotations of AI rumors and secondary public opinion, it systematically analyzes the evolutionary logic, inducing conditions and key risk elements of typical AI rumor incidents. From the perspective of whole-life-cycle risk governance, a multi-dimensional hierarchical situation awareness framework covering the data layer, understanding layer, early warning layer and decision-making layer is constructed. Integrating core modules including public opinion data collection, situational assessment and interpretation, risk feature extraction, and behavioral decision feedback, this system achieves precise perception of secondary public opinion risks triggered by AI rumors.[Result/Conclusion] constructs a relatively complete theoretical model for situation awareness of secondary public opinion risks triggered by AI rumors, which enriches the theoretical system of online public opinion risk governance in the generative artificial intelligence context. Case analysis results verify that the theoretical model proposed in this study possesses sound scientific validity and applicability, and can provide theoretical support and practical references for the governance of secondary public opinion risks arising from AI rumors.[Innovation/Value] This study innovatively constructs a hierarchical situation awareness model oriented to generative AI scenarios, focusing on the secondary derivative risks of AI rumors that are largely overlooked in existing research. It clarifies the multi-layer risk evolution mechanism of public opinion triggered by AI rumors under generative AI contexts and establishes a complete logical framework covering data perception, situational comprehension, risk analysis and early warning decision-making. The research findings improve the theoretical system of online risk governance for generative artificial intelligence and offer theoretical support and practical references for the governance of secondary public opinion risks stemming from AI rumors.[Insufficent/Improvment] This study still has certain limitations. The research mainly focuses on theoretical construction, and the case verification is only carried out based on a single typical AI rumor incident related to disasters. In-depth quantitative analysis concerning model evaluation and risk prediction is insufficient. Future research will integrate more real public opinion cases to improve the model evaluation index system and optimize risk prediction and analysis methods, so as to further promote the application adaptability and practical iteration of the theoretical model. Combined with technical tools and institutional norms, the path of public opinion governance will be optimized, the governance system for secondary public opinion risks of AI rumors will be perfected, and useful support will be provided for maintaining the sound development of cyberspace.关键词
生成式人工智能/AI谣言/次生舆情/风险态势感知/理论模型构建Key words
generative artificial intelligence/AI rumors/secondary public opinion/risk situation awareness/Theoretical Model Construction.引用本文复制引用
张艳丰,文也夫,易臣何.AI谣言次生舆情风险态势感知理论模型构建[EB/OL].(2026-08-24)[2026-09-01].https://chinaxiv.org/abs/202608.00103.学科分类
计算技术、计算机技术
