【摘要】 随着智能媒体技术向教育场域的深度渗透，大学生情感表达呈现出显性化、圈层化和传染性特征，负面情感也通过“信息茧房”形成代偿性传播，进而可能引发群体极化、心理危机等次生风险。文章基于“社会存在决定社会意识”原理，深入剖析了网络情绪的形成机理，运用K最近邻算法构建了网络情绪识别模型，结合负向情绪指标要素设计了可行性预警机制。案例分析与研究结果均表明，该模型具有较高的准确性和稳定性，有助于辅助相关部门及时掌握大学生网络情感动态，为构建完善的网络社会治理体系提供了重要参考。更多还原

【Abstract】 With the deep integration of intelligent media technology into the educational field, college students’ emotional expression has become more explicit, stratified, and contagious. Negative emotions, amplified through “information cocoons”, propagate compensatorily, potentially leading to secondary risksof group polarization and psychological crises. Based on the principle that “social being determines social consciousness”, this paper conducts an in-depth analysis of the formation mechanism of online emotions. A K-nearest neighbors algorithm is employed to construct an online emotion recognition model, and a feasible early-warning mechanism is designed by integrating key indicators of negative emotions. Case studies and research results demonstrate that the proposed model achieves high accuracy and stability, assisting relevant departments in timely understanding of college students’ online emotional dynamics. It provides valuable insights for building a robust governance system for online social environments.更多还原