Zhang Fa, Tang Qian, Chen Jian, Han Na
Department of Management Science and Engineering, Business School, Beijing Institute of Technology, Zhuhai, China.
Research Base of Cross-Border Flow Risk and Governance, Beijing Institute of Technology, Zhuhai, China.
Front Psychol. 2023 Jan 9;13:1066628. doi: 10.3389/fpsyg.2022.1066628. eCollection 2022.
The prevention and control of the coronavirus disease 2019 (COVID-19) epidemic in China has entered a phase of normalization. The basis for evaluating and improving public health strategies is understanding the emotions and concerns of the public. This study establishes a fine-grained emotion-classification model to annotate the emotions of 32,698 Sina Weibo posts related to COVID-19 prevention and control from July 2022 to August 2022. The Dalian University of Technology (DLUT) emotion-classification system was adjusted to form four pairs (eight categories) of bidirectional emotions: good-disgust, joy-sadness, anger-fear, and surprise-anticipation. A lexicon-based method was proposed to classify the emotions of Weibo posts. Based on the selected Weibo posts, the present study analyzed the Chinese public's sentiments and emotions. The results showed that positive sentiment accounted for 51%, negative sentiment accounted for 24%, and neutral sentiment accounted for 25%. Positive sentiments were dominated by good and joy emotions, and negative sentiments were dominated by fear and disgust emotions. The proportion of positive sentiments on official Weibo (accounts belonging to government departments and official media) is significantly higher than that on personal Weibo. Official Weibo users displayed a weak guiding effect on personal users in terms of positive sentiment and the two groups of users were almost completely synchronized in terms of negative sentiment. The linear discriminant analysis (LDA) was performed on the two negative emotions of fear and disgust in the personal posts. The present study found that the emotion of fear was mainly related to COVID-19 infection and death, control of people with positive nucleic acid tests, and the outbreak of local epidemic, while the emotion of disgust was mainly related to the long-term existence of the epidemic, the cost of nucleic acid tests, non-implementation of prevention and control measures, and the occurrence of foreign epidemics. These findings suggest that Chinese attitudes toward epidemic prevention and control are positive and optimistic; however, there is also a notable proportion of fear and disgust. It is expected that this study will help public health administrators to evaluate the effectiveness of possible countermeasures and work toward precise prevention and control of the COVID-19 epidemic.
中国新型冠状病毒肺炎(COVID-19)疫情防控已进入常态化阶段。评估和完善公共卫生策略的基础是了解公众的情绪和关切。本研究建立了一个细粒度情绪分类模型,对2022年7月至2022年8月期间32698条与COVID-19防控相关的新浪微博帖子的情绪进行标注。对大连理工大学(DLUT)情绪分类系统进行调整,形成四对(八类)双向情绪:好-厌恶、喜悦-悲伤、愤怒-恐惧、惊讶-期待。提出了一种基于词典的方法对微博帖子的情绪进行分类。基于所选微博帖子,本研究分析了中国公众的情绪和情感。结果显示,积极情绪占51%,消极情绪占24%,中性情绪占25%。积极情绪以好和喜悦情绪为主,消极情绪以恐惧和厌恶情绪为主。官方微博(政府部门和官方媒体所属账号)上积极情绪的比例显著高于个人微博。官方微博用户在积极情绪方面对个人用户的引导作用较弱,两组用户在消极情绪方面几乎完全同步。对个人帖子中的恐惧和厌恶这两种消极情绪进行线性判别分析(LDA)。本研究发现,恐惧情绪主要与COVID-19感染和死亡、核酸检测阳性人员管控以及局部疫情爆发有关,而厌恶情绪主要与疫情长期存在、核酸检测费用、防控措施未落实以及国外疫情发生有关。这些发现表明,中国民众对疫情防控的态度是积极乐观的;然而,恐惧和厌恶情绪也占有相当比例。预计本研究将有助于公共卫生管理人员评估可能的应对措施的有效性,并朝着精准防控COVID-19疫情努力。
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