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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| Main Authors: | , , , , , |
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| Format: | Article |
| Language: | English |
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Public Library of Science (PLoS)
2023-01-01
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| Series: | PLOS Global Public Health |
| Online Access: | https://doi.org/10.1371/journal.pgph.0001385 |
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| _version_ | 1850265311433981952 |
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| author | Samira Yousefinaghani Rozita Dara Alice Wang Melissa MacKay Andrew Papadopoulos Shayan Sharif |
| author_facet | Samira Yousefinaghani Rozita Dara Alice Wang Melissa MacKay Andrew Papadopoulos Shayan Sharif |
| author_sort | Samira Yousefinaghani |
| collection | DOAJ |
| 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. |
| format | Article |
| id | doaj-art-e96d72d49c744b2dab68780f1f8fa776 |
| institution | OA Journals |
| issn | 2767-3375 |
| language | English |
| publishDate | 2023-01-01 |
| publisher | Public Library of Science (PLoS) |
| record_format | Article |
| series | PLOS Global Public Health |
| spelling | doaj-art-e96d72d49c744b2dab68780f1f8fa7762025-08-20T01:54:27ZengPublic Library of Science (PLoS)PLOS Global Public Health2767-33752023-01-0137e000138510.1371/journal.pgph.0001385Credibility of vaccine-related content on Twitter during COVID-19 pandemic.Samira YousefinaghaniRozita DaraAlice WangMelissa MacKayAndrew PapadopoulosShayan SharifDuring 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.https://doi.org/10.1371/journal.pgph.0001385 |
| spellingShingle | Samira Yousefinaghani Rozita Dara Alice Wang Melissa MacKay Andrew Papadopoulos Shayan Sharif Credibility of vaccine-related content on Twitter during COVID-19 pandemic. PLOS Global Public Health |
| 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 |
| url | https://doi.org/10.1371/journal.pgph.0001385 |
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