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Characterizing Weibo Social Media Posts From Wuhan, China During the Early Stages of the COVID-19 Pandemic: Qualitative Content Analysis
BACKGROUND: The COVID-19 pandemic has reached 40 million confirmed cases worldwide. Given its rapid progression, it is important to examine its origins to better understand how people’s knowledge, attitudes, and reactions have evolved over time. One method is to use data mining of social media conve...
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/PMC7722484/ https://www.ncbi.nlm.nih.gov/pubmed/33175693 http://dx.doi.org/10.2196/24125 |
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author | Xu, Qing Shen, Ziyi Shah, Neal Cuomo, Raphael Cai, Mingxiang Brown, Matthew Li, Jiawei Mackey, Tim |
author_facet | Xu, Qing Shen, Ziyi Shah, Neal Cuomo, Raphael Cai, Mingxiang Brown, Matthew Li, Jiawei Mackey, Tim |
author_sort | Xu, Qing |
collection | PubMed |
description | BACKGROUND: The COVID-19 pandemic has reached 40 million confirmed cases worldwide. Given its rapid progression, it is important to examine its origins to better understand how people’s knowledge, attitudes, and reactions have evolved over time. One method is to use data mining of social media conversations related to information exposure and self-reported user experiences. OBJECTIVE: This study aims to characterize the knowledge, attitudes, and behaviors of social media users located at the initial epicenter of the outbreak by analyzing data from the Sina Weibo platform in Chinese. METHODS: We used web scraping to collect public Weibo posts from December 31, 2019, to January 20, 2020, from users located in Wuhan City that contained COVID-19–related keywords. We then manually annotated all posts using an inductive content coding approach to identify specific information sources and key themes including news and knowledge about the outbreak, public sentiment, and public reaction to control and response measures. RESULTS: We identified 10,159 COVID-19 posts from 8703 unique Weibo users. Among our three parent classification areas, 67.22% (n=6829) included news and knowledge posts, 69.72% (n=7083) included public sentiment, and 47.87% (n=4863) included public reaction and self-reported behavior. Many of these themes were expressed concurrently in the same Weibo post. Subtopics for news and knowledge posts followed four distinct timelines and evidenced an escalation of the outbreak’s seriousness as more information became available. Public sentiment primarily focused on expressions of anxiety, though some expressions of anger and even positive sentiment were also detected. Public reaction included both protective and elevated health risk behavior. CONCLUSIONS: Between the announcement of pneumonia and respiratory illness of unknown origin in late December 2019 and the discovery of human-to-human transmission on January 20, 2020, we observed a high volume of public anxiety and confusion about COVID-19, including different reactions to the news by users, negative sentiment after being exposed to information, and public reaction that translated to self-reported behavior. These findings provide early insight into changing knowledge, attitudes, and behaviors about COVID-19, and have the potential to inform future outbreak communication, response, and policy making in China and beyond. |
format | Online Article Text |
id | pubmed-7722484 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
publisher | JMIR Publications |
record_format | MEDLINE/PubMed |
spelling | pubmed-77224842020-12-11 Characterizing Weibo Social Media Posts From Wuhan, China During the Early Stages of the COVID-19 Pandemic: Qualitative Content Analysis Xu, Qing Shen, Ziyi Shah, Neal Cuomo, Raphael Cai, Mingxiang Brown, Matthew Li, Jiawei Mackey, Tim JMIR Public Health Surveill Original Paper BACKGROUND: The COVID-19 pandemic has reached 40 million confirmed cases worldwide. Given its rapid progression, it is important to examine its origins to better understand how people’s knowledge, attitudes, and reactions have evolved over time. One method is to use data mining of social media conversations related to information exposure and self-reported user experiences. OBJECTIVE: This study aims to characterize the knowledge, attitudes, and behaviors of social media users located at the initial epicenter of the outbreak by analyzing data from the Sina Weibo platform in Chinese. METHODS: We used web scraping to collect public Weibo posts from December 31, 2019, to January 20, 2020, from users located in Wuhan City that contained COVID-19–related keywords. We then manually annotated all posts using an inductive content coding approach to identify specific information sources and key themes including news and knowledge about the outbreak, public sentiment, and public reaction to control and response measures. RESULTS: We identified 10,159 COVID-19 posts from 8703 unique Weibo users. Among our three parent classification areas, 67.22% (n=6829) included news and knowledge posts, 69.72% (n=7083) included public sentiment, and 47.87% (n=4863) included public reaction and self-reported behavior. Many of these themes were expressed concurrently in the same Weibo post. Subtopics for news and knowledge posts followed four distinct timelines and evidenced an escalation of the outbreak’s seriousness as more information became available. Public sentiment primarily focused on expressions of anxiety, though some expressions of anger and even positive sentiment were also detected. Public reaction included both protective and elevated health risk behavior. CONCLUSIONS: Between the announcement of pneumonia and respiratory illness of unknown origin in late December 2019 and the discovery of human-to-human transmission on January 20, 2020, we observed a high volume of public anxiety and confusion about COVID-19, including different reactions to the news by users, negative sentiment after being exposed to information, and public reaction that translated to self-reported behavior. These findings provide early insight into changing knowledge, attitudes, and behaviors about COVID-19, and have the potential to inform future outbreak communication, response, and policy making in China and beyond. JMIR Publications 2020-12-07 /pmc/articles/PMC7722484/ /pubmed/33175693 http://dx.doi.org/10.2196/24125 Text en ©Qing Xu, Ziyi Shen, Neal Shah, Raphael Cuomo, Mingxiang Cai, Matthew Brown, Jiawei Li, Tim Mackey. Originally published in JMIR Public Health and Surveillance (http://publichealth.jmir.org), 07.12.2020. 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 JMIR Public Health and Surveillance, is properly cited. The complete bibliographic information, a link to the original publication on http://publichealth.jmir.org, as well as this copyright and license information must be included. |
spellingShingle | Original Paper Xu, Qing Shen, Ziyi Shah, Neal Cuomo, Raphael Cai, Mingxiang Brown, Matthew Li, Jiawei Mackey, Tim Characterizing Weibo Social Media Posts From Wuhan, China During the Early Stages of the COVID-19 Pandemic: Qualitative Content Analysis |
title | Characterizing Weibo Social Media Posts From Wuhan, China During the Early Stages of the COVID-19 Pandemic: Qualitative Content Analysis |
title_full | Characterizing Weibo Social Media Posts From Wuhan, China During the Early Stages of the COVID-19 Pandemic: Qualitative Content Analysis |
title_fullStr | Characterizing Weibo Social Media Posts From Wuhan, China During the Early Stages of the COVID-19 Pandemic: Qualitative Content Analysis |
title_full_unstemmed | Characterizing Weibo Social Media Posts From Wuhan, China During the Early Stages of the COVID-19 Pandemic: Qualitative Content Analysis |
title_short | Characterizing Weibo Social Media Posts From Wuhan, China During the Early Stages of the COVID-19 Pandemic: Qualitative Content Analysis |
title_sort | characterizing weibo social media posts from wuhan, china during the early stages of the covid-19 pandemic: qualitative content analysis |
topic | Original Paper |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7722484/ https://www.ncbi.nlm.nih.gov/pubmed/33175693 http://dx.doi.org/10.2196/24125 |
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