Research on university public opinion management based on multi AI model collaborative decision making and optimization scheme
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摘要：
人工智能(artifcial itelligence,AI)的引人为高校舆情分析和管理提供了新的视角和工具,但现有AI在决策过程中缺乏透明性和可解释性,加之受限于单一模型,降低了决策方案的普适价值与优化潜力.针对以上问题,探讨了如何通过多A1模型协同决策与优化，提高高校舆情管理的效率和质量.首先选取2023年高校舆情热点案例,构建专注于高校舆情领域的垂直数据集,并利用AI技术进行数据分析和特征提取.其次,为增强AI评价过程中的可解释性和公平性,构筑多维度多角色评价体系,提出舆情智能指数(POI)和智能迭代优化指数(IIOID)，用于量化评估AI模型在舆情管理中的表现和自我修正能力.最终,通过实验发现,多AI模型协同决策与优化方案相较于单一AI模型,能显著提高AI在舆情管理领域生成决策方案的效率和质量.
The introduction of artificial intelligence (AI) provides a new perspective and tool for analyzing and managing public opinion in colleges and universities. However, the existing AI lacks transparency and interpretability in the decision-mak-ing process, and is limited by a single model, which reduces the universal value and optrmization potential of the decision-mak-ing scheme, In response to the above issues, this article explores how to improve the efficieney and the quality of public opinion management in universities through collaborative decision-making and optimization using muliple AI models. Firsuly,seleet the hot cases of publie opinion in universtties in 2023, construct a vertical dataset foeusing on the field of publie opinion in universi-ties, and use AI technology for data analysis and feature extraction, Secondly, in order to enhance the interpretability and fair-ness of the AI evaluation process, a multidimensional and multi role evaluation system is constructed, and the Public Opinion Intelligence Index(POII) and Intelligent Iterative Optimization Index(IlOI) are proposed to quantitatively evaluate AI models abilties of perforance and seIf correction in public opinion management. Ultimately, through experiments, it was found that collaborative decision-making and optimization solutions with multiple AI models can significantly improve the efficieney and quality of AI in generating deeision-making solutions in the field of public opinion management compared to a single AI model.
作者:
何静，陈逸然，戴田宇
He Jingl，Chen Yiran，Dai Tianyu
机构地区：
北京航空航天大学 a.人文与社会科学高等研究院；b.人工智能学院；南昌大学数学与计算机学院
引用本文：
何静，陈逸然，戴田宇。基于多AI模型协同决策与优化方案的高校舆情管理研究[J].河南师范大学学报(自然科学版),2026,54(1):92-98.(He Jing,Chen Yiran, Dai Tianyu. Research on university public opinion management based on muli AI model collaborative decision making and optimization scheme [J].Joural of Henan Normal University(Natural Science Edition),2026,54(1):92-98.DOI:10.16366/j.cnki.1000-2367.2024.08.23.0001.)
基金：
国家自然科学基金；北京市教育科学“十 四 五”规划课题；北京市社会科学基金
关键词：
高校舆情；人工智能；多模型协同；决策优化
university public opinion; artificial intelligence; multi model collaboration; decision optimization
分类号：
G206
