"DOWNSCALING" OR "NAVIGATION": AIGC FACILITATING THE RESEARCH ON PUBLIC OPINION RESPONSE IN ENTERPRISE EMERGENCIES

Abstract

This study aims to address the current dilemma in corporate emergency online public opinion governance: overemphasis on technical model analysis, insufficient empirical verification, and unclear causal relationship between AIGC technology and governance effectiveness. Taking the "Ailao Mountain Incident" as a case study, this research adopts multi-source data collection, comparative modeling analysis, cross-platform dissemination simulation, and controlled experiments. Integrating the three-dimensional analytical framework (intensity, temporality, spatiality) of Event System Theory (EST), it explores the information characteristics, dissemination patterns, interaction mechanisms, and innovative paths of AIGC in corporate emergency public opinion response.The results indicate that: First, there exists a significant positive correlation between the intensity of corporate emergencies and AIGC's public opinion governance effectiveness. In highintensity events, AIGC demonstrates advantages in monitoring coverage, judgment precision, and content production efficiency. Second, AIGC's effectiveness presents stagespecific adaptive characteristics as the event evolves over time: during the outbreak phase, it focuses on aggregating fragmented information and identifying key points; during the diffusion phase, it emphasizes tracking dissemination paths and risk modeling; during the stabilization phase, it shifts to long-tail monitoring and effect evaluation. Third, the wider the spatial diffusion scope of the event, the more critical AIGC's role becomes in integrating heterogeneous spatial information and coordinating cross-domain governance. However, AIGC also carries the risk of "technological backlash."This study not only enriches the application dimension of EST in public opinion research but also provides insights for enterprises to transform their public opinion management from the "passive response" model to the new paradigm of "proactive prevention and control."