Researchers in this study explore the psychological impacts of COVID-19 on people's mental health, aiming to assist policymakers and clinical practitioners in developing actionable policies and providing timely services to affected populations. To achieve this goal, the researchers analyze Weibo posts from 17,865 active users using machine learning predictive models based on the approach of Online Ecological Recognition (OER). They calculate word frequency, emotional indicators, and cognitive indicators to examine the differences in the same group before and after the declaration of COVID-19.
The results indicate that negative emotions, such as anxiety, depression, and indignation, increased, while the scores of positive emotions, such as happiness, and life satisfaction decreased. People were more concerned about their health and family, while less about leisure and friends. The study's findings could help policymakers plan and fight against COVID-19 effectively, improve the stability of popular feelings, and prepare clinical practitioners to deliver corresponding therapy foundations for the risk groups and affected people.