The development of a college students’ psychological management system has become an essential indicator to monitor and prevent the psychological crisis. University student management databases accumulate massive data, but the conventional data processing tasks are restricted to simple statistical analysis, storage, and query management. This paper discusses the application of big data technology for the current psychological management system by investigating psychological crisis screening indicators. Data mining techniques are used to realize the dynamic management of psychological early warning data, real-time monitoring of high-risk groups’ psychology, and improvement of the accuracy and effectiveness of early identification and warning of students’ psychological crisis. Based on a combination of qualitative and quantitative analysis, we conduct a series of studies on three typical types of network public opinions, i.e., Internet rumors, online public opinions of college students, and emergent public health incidents in terms of the transmission mechanism, early warning, and decision-making mechanism, as well as the evolution mechanism of the network public opinion.

中文翻译：

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基于数据挖掘的大学生心理危机预测

发展大学生心理管理体系已成为监测和预防心理危机的重要指标。大学生管理数据库积累了大量数据，但是常规的数据处理任务仅限于简单的统计分析，存储和查询管理。本文通过调查心理危机筛查指标，探讨了大数据技术在当前心理管理系统中的应用。数据挖掘技术用于实现心理预警数据的动态管理，对高危人群心理的实时监控，提高对学生心理危机的早期识别预警的准确性和有效性。基于定性和定量分析的结合，