Author(s)

Mengnan Zhang

Corresponding Author

Mengnan Zhang

ABSTRACT

The psychological status of the public since the outbreak is more negative, and the negative emotion increase significantly. From the perspective of longitudinal research, this study applied sentiment analysis and text mining techniques to mine the basic emotions expressed in microblog posts. And addressed the research problem about the influencing factors and key events of negative emotions. This study shows a new method reference for psychological research and provides ideas for using social media to dynamically detect and intervene in public mental health.

KEYWORDS

Negative emotion changes, Lockdown, Basic emotion theory, Sentiment analysis, Dynamic topic model analysis