生成式人工智能背景下网络舆情智能治理：理论建构与实现路径

Intelligent Governance of Online Public Opinion in the Context of AIGC: Theoretical Construction and Implementation Pathways

摘要: 生成式人工智能(AIGC)的快速迭代正深度重塑信息传播生态，推动人类社会加速步入智能传播时代。作为影响网络社会运行和公共治理转型的重要变量，AIGC不仅改变了网络信息生产方式和传播机制，也改变了网络舆情风险生成逻辑，使传统网络舆情治理模式面临适应性挑战。本文基于智能治理、协同治理和风险治理等理论视角，从现实逻辑、理论建构和实现路径三个层面对AIGC时代网络舆情智能治理展开分析。研究认为，网络舆情智能治理并非人工智能技术与传统治理模式的简单结合，而是在智能传播环境变化基础上形成的新型治理范式，其理论框架体现为数据驱动、智能研判、人机协同和多元共治。推进网络舆情智能治理，需要提升智能感知能力、强化智能研判能力、优化人机协同机制和完善多元协同机制，并在伦理规制与制衡机制下，实现技术赋能与治理价值的统一。

Abstract: The rapid iteration of Artificial Intelligence Generated Content (AIGC) is profoundly reshaping the information communication ecosystem, accelerating humanity’s entry into the era of intelligent communication. As a critical variable influencing the operation of online society and the transformation of public governance, AIGC has not only transformed the modes of online information production and dissemination mechanisms but also fundamentally altered the generative logic of online public opinion risks, subjecting traditional governance models to adaptive challenges. Drawing upon the theoretical perspectives of intelligent governance, collaborative governance, and risk governance, this paper conducts a systematic analysis of intelligent governance of online public opinion in the AIGC era across three dimensions: practical logic, theoretical construction, and implementation pathways. The study posits that intelligent governance of online public opinion is not a mere combination of artificial intelligence technologies with traditional governance models, but rather a novel governance paradigm emerging from the transformative changes in the intelligent communication environment. Its theoretical framework is embodied in four pillars: data-driven decision-making, intelligent assessment, human-machine collaboration, and pluralistic co-governance. Advancing intelligent governance of online public opinion requires enhancing intelligent perception capabilities, strengthening intelligent assessment capabilities, optimizing human-machine collaboration mechanisms, and improving pluralistic coordination mechanisms, while under the framework of ethical regulation and checks-and-balances mechanisms, achieving the integration of technological empowerment and governance values.