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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...

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Detalles Bibliográficos
Autores principales: Dong, Wei, Tao, Jinhu, Xia, Xiaolin, Ye, Lin, Xu, Hanli, Jiang, Peiye, Liu, Yangyang
Formato: Online Artículo Texto
Lenguaje:English
Publicado: JMIR Publications 2020
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.
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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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