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Credibility of vaccine-related content on Twitter during COVID-19 pandemic

During national COVID-19 vaccine campaigns, people continuously engaged on Twitter to receive updates on the latest public health information, and to discuss and share their experiences. During this time, the spread of misinformation was widespread, which threatened the uptake of vaccines. It is the...

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Autores principales: Yousefinaghani, Samira, Dara, Rozita, Wang, Alice, MacKay, Melissa, Papadopoulos, Andrew, Sharif, Shayan
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10355402/
https://www.ncbi.nlm.nih.gov/pubmed/37467276
http://dx.doi.org/10.1371/journal.pgph.0001385
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author Yousefinaghani, Samira
Dara, Rozita
Wang, Alice
MacKay, Melissa
Papadopoulos, Andrew
Sharif, Shayan
author_facet Yousefinaghani, Samira
Dara, Rozita
Wang, Alice
MacKay, Melissa
Papadopoulos, Andrew
Sharif, Shayan
author_sort Yousefinaghani, Samira
collection PubMed
description During national COVID-19 vaccine campaigns, people continuously engaged on Twitter to receive updates on the latest public health information, and to discuss and share their experiences. During this time, the spread of misinformation was widespread, which threatened the uptake of vaccines. It is therefore critical to understand the reasons behind vaccine misinformation and strategies to mitigate it. The current research aimed to understand the content of misleading tweets and the characteristics of their corresponding accounts. We performed a machine learning approach to identify misinformation in vaccine-related tweets, and calculated the demographic, engagement metrics and bot-like activities of corresponding accounts. We found critical periods where high amounts of misinformation coincided with important vaccine announcements, such as emergency approvals of vaccines. Moreover, we found Asian countries had a lower percentage of misinformation shared compared to Europe and North America. Our results showed accounts spreading misinformation had an overall 10% greater likelihood of bot activity and 15% more astroturf bot activity than accounts spreading accurate information. Furthermore, we found that accounts spreading misinformation had five times fewer followers and three times fewer verified badges than fact-sharing accounts. The findings of this study may help authorities to develop strategies to fight COVID-19 vaccine misinformation and improve vaccine uptake.
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spelling pubmed-103554022023-07-20 Credibility of vaccine-related content on Twitter during COVID-19 pandemic Yousefinaghani, Samira Dara, Rozita Wang, Alice MacKay, Melissa Papadopoulos, Andrew Sharif, Shayan PLOS Glob Public Health Research Article During national COVID-19 vaccine campaigns, people continuously engaged on Twitter to receive updates on the latest public health information, and to discuss and share their experiences. During this time, the spread of misinformation was widespread, which threatened the uptake of vaccines. It is therefore critical to understand the reasons behind vaccine misinformation and strategies to mitigate it. The current research aimed to understand the content of misleading tweets and the characteristics of their corresponding accounts. We performed a machine learning approach to identify misinformation in vaccine-related tweets, and calculated the demographic, engagement metrics and bot-like activities of corresponding accounts. We found critical periods where high amounts of misinformation coincided with important vaccine announcements, such as emergency approvals of vaccines. Moreover, we found Asian countries had a lower percentage of misinformation shared compared to Europe and North America. Our results showed accounts spreading misinformation had an overall 10% greater likelihood of bot activity and 15% more astroturf bot activity than accounts spreading accurate information. Furthermore, we found that accounts spreading misinformation had five times fewer followers and three times fewer verified badges than fact-sharing accounts. The findings of this study may help authorities to develop strategies to fight COVID-19 vaccine misinformation and improve vaccine uptake. Public Library of Science 2023-07-19 /pmc/articles/PMC10355402/ /pubmed/37467276 http://dx.doi.org/10.1371/journal.pgph.0001385 Text en © 2023 Yousefinaghani et al 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 author and source are credited.
spellingShingle Research Article
Yousefinaghani, Samira
Dara, Rozita
Wang, Alice
MacKay, Melissa
Papadopoulos, Andrew
Sharif, Shayan
Credibility of vaccine-related content on Twitter during COVID-19 pandemic
title Credibility of vaccine-related content on Twitter during COVID-19 pandemic
title_full Credibility of vaccine-related content on Twitter during COVID-19 pandemic
title_fullStr Credibility of vaccine-related content on Twitter during COVID-19 pandemic
title_full_unstemmed Credibility of vaccine-related content on Twitter during COVID-19 pandemic
title_short Credibility of vaccine-related content on Twitter during COVID-19 pandemic
title_sort credibility of vaccine-related content on twitter during covid-19 pandemic
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10355402/
https://www.ncbi.nlm.nih.gov/pubmed/37467276
http://dx.doi.org/10.1371/journal.pgph.0001385
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