Analysis model of college students' mental health based on online community topic mining and emotion analysis in novel coronavirus epidemic situation - Lu, Zuqin (Frontiers in Public Health, 2022)
Under the epidemic situation in COVID-19, university students have different levels of anxiety, depression and other psychological problems, and different levels of anxiety, depression and other influencing factors are not exactly the same. Therefore, universities and relevant departments should carry out accurate psychological health education for university students. Through research, this paper found that students' psychological problems during the COVID-19 epidemic mainly reflected in four aspects: depression, interpersonal relationship, sleep and eating disorder and compulsive behavior. Through the discussion of family of origin, self-awareness and motivation attribution, and social pressure, this paper analyzed the causes of psychological problems. The information resources of the network are usually unstructured data, and the text information, as the most typical unstructured data, occupies a large proportion. Moreover, these text information often contain users' emotional inclination for hot events. In this paper, a data preprocessing system is designed, and three data preprocessing rules are defined, including expression data conversion rules, data deduplication rules and invalid data cleaning rules. The characteristics of online community text data are analyzed, and the text feature extraction method is selected according to its characteristics. The results of this study show that the proportion of university students with psychological problems is about 23%, which is slightly higher than the research results during the non-epidemic period. This paper has made some contributions to the college students to master the methods of self-regulation, strengthen physical exercise, strengthen physical fitness, establish and improve the defense mechanism, and alleviate psychological conflicts and pressures.