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Public Emotions and Rumors Spread During the COVID-19 Epidemic in China: Web-Based Correlation Study
BACKGROUND: Various online rumors have led to inappropriate behaviors among the public in response to the COVID-19 epidemic in China. These rumors adversely affect people’s physical and mental health. Therefore, a better understanding of the relationship between public emotions and rumors during the...
Autores principales: | , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
JMIR Publications
2020
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7690969/ https://www.ncbi.nlm.nih.gov/pubmed/33112757 http://dx.doi.org/10.2196/21933 |
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author | Dong, Wei Tao, Jinhu Xia, Xiaolin Ye, Lin Xu, Hanli Jiang, Peiye Liu, Yangyang |
author_facet | Dong, Wei Tao, Jinhu Xia, Xiaolin Ye, Lin Xu, Hanli Jiang, Peiye Liu, Yangyang |
author_sort | Dong, Wei |
collection | PubMed |
description | BACKGROUND: Various online rumors have led to inappropriate behaviors among the public in response to the COVID-19 epidemic in China. These rumors adversely affect people’s physical and mental health. Therefore, a better understanding of the relationship between public emotions and rumors during the epidemic may help generate useful strategies for guiding public emotions and dispelling rumors. OBJECTIVE: This study aimed to explore whether public emotions are related to the dissemination of online rumors in the context of COVID-19. METHODS: We used the web-crawling tool Scrapy to gather data published by People’s Daily on Sina Weibo, a popular social media platform in China, after January 8, 2020. Netizens’ comments under each Weibo post were collected. Nearly 1 million comments thus collected were divided into 5 categories: happiness, sadness, anger, fear, and neutral, based on the underlying emotional information identified and extracted from the comments by using a manual identification process. Data on rumors spread online were collected through Tencent’s Jiaozhen platform. Time-lagged cross-correlation analyses were performed to examine the relationship between public emotions and rumors. RESULTS: Our results indicated that the angrier the public felt, the more rumors there would likely be (r=0.48, P<.001). Similar results were observed for the relationship between fear and rumors (r=0.51, P<.001) and between sadness and rumors (r=0.47, P<.001). Furthermore, we found a positive correlation between happiness and rumors, with happiness lagging the emergence of rumors by 1 day (r=0.56, P<.001). In addition, our data showed a significant positive correlation between fear and fearful rumors (r=0.34, P=.02). CONCLUSIONS: Our findings confirm that public emotions are related to the rumors spread online in the context of COVID-19 in China. Moreover, these findings provide several suggestions, such as the use of web-based monitoring methods, for relevant authorities and policy makers to guide public emotions and behavior during this public health emergency. |
format | Online Article Text |
id | pubmed-7690969 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
publisher | JMIR Publications |
record_format | MEDLINE/PubMed |
spelling | pubmed-76909692020-11-30 Public Emotions and Rumors Spread During the COVID-19 Epidemic in China: Web-Based Correlation Study Dong, Wei Tao, Jinhu Xia, Xiaolin Ye, Lin Xu, Hanli Jiang, Peiye Liu, Yangyang J Med Internet Res Original Paper BACKGROUND: Various online rumors have led to inappropriate behaviors among the public in response to the COVID-19 epidemic in China. These rumors adversely affect people’s physical and mental health. Therefore, a better understanding of the relationship between public emotions and rumors during the epidemic may help generate useful strategies for guiding public emotions and dispelling rumors. OBJECTIVE: This study aimed to explore whether public emotions are related to the dissemination of online rumors in the context of COVID-19. METHODS: We used the web-crawling tool Scrapy to gather data published by People’s Daily on Sina Weibo, a popular social media platform in China, after January 8, 2020. Netizens’ comments under each Weibo post were collected. Nearly 1 million comments thus collected were divided into 5 categories: happiness, sadness, anger, fear, and neutral, based on the underlying emotional information identified and extracted from the comments by using a manual identification process. Data on rumors spread online were collected through Tencent’s Jiaozhen platform. Time-lagged cross-correlation analyses were performed to examine the relationship between public emotions and rumors. RESULTS: Our results indicated that the angrier the public felt, the more rumors there would likely be (r=0.48, P<.001). Similar results were observed for the relationship between fear and rumors (r=0.51, P<.001) and between sadness and rumors (r=0.47, P<.001). Furthermore, we found a positive correlation between happiness and rumors, with happiness lagging the emergence of rumors by 1 day (r=0.56, P<.001). In addition, our data showed a significant positive correlation between fear and fearful rumors (r=0.34, P=.02). CONCLUSIONS: Our findings confirm that public emotions are related to the rumors spread online in the context of COVID-19 in China. Moreover, these findings provide several suggestions, such as the use of web-based monitoring methods, for relevant authorities and policy makers to guide public emotions and behavior during this public health emergency. JMIR Publications 2020-11-25 /pmc/articles/PMC7690969/ /pubmed/33112757 http://dx.doi.org/10.2196/21933 Text en ©Wei Dong, Jinhu Tao, Xiaolin Xia, Lin Ye, Hanli Xu, Peiye Jiang, Yangyang Liu. Originally published in the Journal of Medical Internet Research (http://www.jmir.org), 25.11.2020. https://creativecommons.org/licenses/by/4.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work, first published in the Journal of Medical Internet Research, is properly cited. The complete bibliographic information, a link to the original publication on http://www.jmir.org/, as well as this copyright and license information must be included. |
spellingShingle | Original Paper Dong, Wei Tao, Jinhu Xia, Xiaolin Ye, Lin Xu, Hanli Jiang, Peiye Liu, Yangyang Public Emotions and Rumors Spread During the COVID-19 Epidemic in China: Web-Based Correlation Study |
title | Public Emotions and Rumors Spread During the COVID-19 Epidemic in China: Web-Based Correlation Study |
title_full | Public Emotions and Rumors Spread During the COVID-19 Epidemic in China: Web-Based Correlation Study |
title_fullStr | Public Emotions and Rumors Spread During the COVID-19 Epidemic in China: Web-Based Correlation Study |
title_full_unstemmed | Public Emotions and Rumors Spread During the COVID-19 Epidemic in China: Web-Based Correlation Study |
title_short | Public Emotions and Rumors Spread During the COVID-19 Epidemic in China: Web-Based Correlation Study |
title_sort | public emotions and rumors spread during the covid-19 epidemic in china: web-based correlation study |
topic | Original Paper |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7690969/ https://www.ncbi.nlm.nih.gov/pubmed/33112757 http://dx.doi.org/10.2196/21933 |
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