The Daily Rhythmic Changes of Undergraduate Students’ Emotions: An Analysis Based on Tencent Tweets - Liu, Run-Xiang; Liu, Huan (Frontiers in Psychology, 2022)
Emotional stability is of great importance for undergraduates and has significant predictive power for mental health. Emotions are associated with individuals’ daily lives and routines. Undergraduates commonly post their opinions and feelings on social networks, providing a huge amount of data for studying their emotional states and rhythms. Based on the construction of the emotion dictionary of undergraduates’ Tencent tweets—a social network for users to share their life situations and express their emotions and feelings to their friends—we used big data text analysis technology to analyze the emotion words in 45,996 Tencent tweets published by 894 undergraduates. Then, we used hierarchical linear modeling to further analyze the daily rhythms of undergraduate students’ emotions and how demographic variables are associated with the daily rhythmic changes. The results were as follows: (1) Undergraduates tweeted about more positive emotions than negative emotions (love was most common and fear was the least common); (2) The emotions in undergraduates’ tweets changed considerably from 1 a.m. to 6 a.m., but were fairly stable during the day; (3) There was a rising trend in the frequency of using emotion words in Tencent tweets during the day as each hour progressed, and there was a higher increase in positive emotion than negative emotion; and (4) Demographic variables such as gender, grade, place of origin, family economic status, and structural status, were correlated with the mention of emotions in Tencent tweets. The results of the present study provided emotion expression in social networks in Chinese collectivist culture. This study added new evidence to support the notion that positive and negative emotions are independent dimensions.