Online Evaluation Method of College Students’ Mental Health Based on Campus Network Text Mining

Abstract

Aiming at the problem that the mental health of contemporary college students is affected by many parties, and the evaluation accuracy and evaluation effect are poor, an online evaluation method of college students’ mental health based on campus network text mining is proposed. Mining and analyzing the association rules of the association features between texts, analyzing the monitoring quantitative index of the online evaluation of college students’ mental health; based on the regional transfer coefficient of existing mental health text information, the influencing factors of college students’ mental health are determined, and the online evaluation model of college students’ mental health is constructed. The membership degree of the factors is comprehensively calculated, and the corresponding fuzzy consistent matrix is used to compare the quantitative results of the index scales, and the interval number judgment matrix is constructed, which corresponds to the interval number weight of each secondary evaluation index one-to-one. The weight of the indicators is divided into the mental health assessment level, and the online assessment of college students’ mental health is completed. The experimental results show that the evaluation accuracy of the design method is more than 97.36%, the recall rate is more than 97%, and the highest packet loss rate is less than 0.3%, which proves that the online evaluation results of college students in this method are more accurate and that the accuracy and effect of the online evaluation of college students’ mental health are improved.