Research on the Collaborative Governance Model of AI Agents for University Network Public Opinion under the Concept of Management-Education Integration

Abstract

The governance of university network public opinion faces multiple challenges, including information fragmentation, carrier diversification, and inadequate collaboration. Traditional management models exhibit structural limitations in terms of monitoring coverage, depth of analysis, and response timeliness. Grounded in the concept of Management-Education Integration, this study explores the collaborative model of AI agents in the governance of university network public opinion, presenting a systematic analysis across four dimensions: theoretical perspective, structural design, mechanism construction, and operational model. The research reveals the inherent coupling between Management-Education Integration and technological empowerment, constructs a multi-stakeholder collaborative framework mediated by algorithms, proposes a four-in-one guarantee system encompassing departmental collaboration, research-practice collaboration, human-AI collaboration, and regulatory collaboration, and refines a three-in-one operational mechanism integrating digital-intelligent perception with educational recognition, collaborative regulation with flexible guidance, and efficacy evaluation with model iteration. The study indicates that AI agents can transform unstructured public opinion into structured educational topics, achieving the dual objectives of maintaining online order and promoting student development through human-machine collaboration.