A study on the impact of COVID-19 class suspension on college students’ emotions based on affective computing model

Abstract

Abstract This paper uses affective computing and mood measures to calculate the negative emotional status of college students during school closures. The psychological data of university students at the University of H were counted using the affective computing model and psychometric methods, the frequency of their negative emotion words was mined, and the changes of each psychometric index were analyzed in terms of the time dimension, stressor, anxiety status, and emotional state, respectively. The epidemic closure period had a great negative impact on students. From January 20 to December 20, 2021, college students’ positive mood characteristic value declined. The negative mood characteristic value increased, and the negative mood characteristic value was always higher than the positive mood characteristic value. Finally, the negative mood characteristic value of 0.27 was much higher than the positive mood characteristic value of 0.07, and there were various discomforts such as about 40% of people were nervous, depressed, lacked motivation, and had diminished interest; at the same time, feelings of difficulty in accomplishing goals, failure, fear, anxiety, and frustration emerged. The epidemic closure greatly impacted students’ psychology, and students’ psychological problems need to be taken seriously and receive timely guidance.