Center for Medical Statistics, Informatics and Intelligent Systems.
Psychological Sciences Research Institute.
Emotion. 2023 Apr;23(3):844-858. doi: 10.1037/emo0001111. Epub 2022 Jul 4.
The COVID-19 pandemic has exposed the world's population to unprecedented health threats and changes to social life. High uncertainty about the novel disease and its social and economic consequences, together with increasingly stringent governmental measures against the spread of the virus, likely elicited strong emotional responses. We analyzed the digital traces of emotional expressions in tweets during 5 weeks after the start of outbreaks in 18 countries and six different languages. We observed an early strong upsurge of anxiety-related terms in all countries, which was related to the growth in cases and increases in the stringency of governmental measures. Anxiety expression gradually relaxed once stringent measures were in place, possibly indicating that people were reassured. Sadness terms rose and anger terms decreased with or after an increase in the stringency of measures and remained stable as long as measures were in place. Positive emotion words only decreased slightly and briefly in a few countries. Our results reveal some of the most enduring changes in emotional expression observed in long periods of social media data. Such sustained emotional expression could indicate that interactions between users led to the emergence of collective emotions. Words that frequently occurred in tweets suggest a shift in topics of conversation across all emotions, from political ones in 2019, to pandemic related issues during the outbreak, including everyday life changes, other people, and health. This kind of time-sensitive analyses of large-scale samples of emotional expression have the potential to inform risk communication. (PsycInfo Database Record (c) 2023 APA, all rights reserved).
COVID-19 大流行使世界人口面临前所未有的健康威胁和社会生活的变化。人们对这种新型疾病及其社会和经济后果的高度不确定性,以及各国政府为阻止病毒传播而采取的日益严格的措施,可能引发了强烈的情绪反应。我们分析了在 18 个国家和六种不同语言中,疫情爆发后 5 周内,推特上情绪表达的数字痕迹。我们观察到,所有国家的焦虑相关词汇都出现了早期的强烈上升,这与病例的增加和政府措施的严格程度的增加有关。一旦采取了严格的措施,焦虑情绪的表达就会逐渐放松,这可能表明人们感到放心。随着措施的实施或之后,悲伤的词汇增加,愤怒的词汇减少,而只要措施到位,悲伤的词汇就会保持稳定。积极的情绪词汇只在少数几个国家略有短暂下降。我们的研究结果揭示了社交媒体数据中观察到的一些最持久的情绪表达变化。这种持续的情绪表达可能表明,用户之间的互动导致了集体情绪的出现。在推文中经常出现的词汇表明,所有情绪的话题都发生了转变,从 2019 年的政治话题,到疫情期间与大流行相关的问题,包括日常生活变化、他人和健康。这种对大规模情绪表达样本的时间敏感分析有可能为风险沟通提供信息。(PsycInfo 数据库记录(c)2023 APA,保留所有权利)。