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China public emotion analysis under normalization of COVID-19 epidemic: Using Sina Weibo

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-classi...

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Autores principales: Zhang, Fa, Tang, Qian, Chen, Jian, Han, Na
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9870544/
https://www.ncbi.nlm.nih.gov/pubmed/36698592
http://dx.doi.org/10.3389/fpsyg.2022.1066628
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author Zhang, Fa
Tang, Qian
Chen, Jian
Han, Na
author_facet Zhang, Fa
Tang, Qian
Chen, Jian
Han, Na
author_sort Zhang, Fa
collection PubMed
description 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.
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spelling pubmed-98705442023-01-24 China public emotion analysis under normalization of COVID-19 epidemic: Using Sina Weibo Zhang, Fa Tang, Qian Chen, Jian Han, Na Front Psychol Psychology 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. Frontiers Media S.A. 2023-01-09 /pmc/articles/PMC9870544/ /pubmed/36698592 http://dx.doi.org/10.3389/fpsyg.2022.1066628 Text en Copyright © 2023 Zhang, Tang, Chen and Han. https://creativecommons.org/licenses/by/4.0/This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
spellingShingle Psychology
Zhang, Fa
Tang, Qian
Chen, Jian
Han, Na
China public emotion analysis under normalization of COVID-19 epidemic: Using Sina Weibo
title China public emotion analysis under normalization of COVID-19 epidemic: Using Sina Weibo
title_full China public emotion analysis under normalization of COVID-19 epidemic: Using Sina Weibo
title_fullStr China public emotion analysis under normalization of COVID-19 epidemic: Using Sina Weibo
title_full_unstemmed China public emotion analysis under normalization of COVID-19 epidemic: Using Sina Weibo
title_short China public emotion analysis under normalization of COVID-19 epidemic: Using Sina Weibo
title_sort china public emotion analysis under normalization of covid-19 epidemic: using sina weibo
topic Psychology
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9870544/
https://www.ncbi.nlm.nih.gov/pubmed/36698592
http://dx.doi.org/10.3389/fpsyg.2022.1066628
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