International Journal of Environmental Research and Public Health · 2020 · 1.9K citations · 24 references
Social SciencesBehavioral SciencesPsychologyBehavioral HealthHealth PsychologySocial Media AnalyticsAffective ComputingEmotion RecognitionPredictive Health ModelingSentiment AnalysisSocial MediaSocial ThreatEmotion DetectionEmotionsHealth-related Event DetectionLife Satisfaction MeasurementMachine Learning Risk ModelsTextual Sentiment Analysis
COVID‑19 has caused widespread psychological consequences. The study aims to examine COVID‑19’s impact on mental health to inform policy makers and clinicians. The authors analyzed 17,865 Weibo posts using machine‑learning–based Online Ecological Recognition, computing emotional and cognitive indicators and conducting sentiment analysis and paired‑sample t‑tests before and after the January 20 declaration. Negative emotions and social‑risk sensitivity rose while positive emotions and life satisfaction fell, indicating short‑term psychological shifts that can guide policy and clinical interventions.
COVID-19 (Corona Virus Disease 2019) has significantly resulted in a large number of psychological consequences. The aim of this study is to explore the impacts of COVID-19 on people’s mental health, to assist policy makers to develop actionable policies, and help clinical practitioners (e.g., social workers, psychiatrists, and psychologists) provide timely services to affected populations. We sample and analyze the Weibo posts from 17,865 active Weibo users using the approach of Online Ecological Recognition (OER) based on several machine-learning predictive models. We calculated word frequency, scores of emotional indicators (e.g., anxiety, depression, indignation, and Oxford happiness) and cognitive indicators (e.g., social risk judgment and life satisfaction) from the collected data. The sentiment analysis and the paired sample t-test were performed to examine the differences in the same group before and after the declaration of COVID-19 on 20 January, 2020. The results showed that negative emotions (e.g., anxiety, depression and indignation) and sensitivity to social risks increased, while the scores of positive emotions (e.g., Oxford happiness) and life satisfaction decreased. People were concerned more about their health and family, while less about leisure and friends. The results contribute to the knowledge gaps of short-term individual changes in psychological conditions after the outbreak. It may provide references for policy makers to plan and fight against COVID-19 effectively by improving stability of popular feelings and urgently prepare clinical practitioners to deliver corresponding therapy foundations for the risk groups and affected people.
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Clinical features of patients infected with 2019 novel coronavirus in Wuhan, China
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