Negative COVID-19 Vaccine Information on Twitter: Content Analysis
BackgroundSocial media platforms, such as Facebook, Instagram, Twitter, and YouTube, have a role in spreading anti-vaccine opinion and misinformation. Vaccines have been an important component of managing the COVID-19 pandemic, so content that discourages vaccination is gener...
| Main Authors: | , , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
JMIR Publications
2022-08-01
|
| Series: | JMIR Infodemiology |
| Online Access: | https://infodemiology.jmir.org/2022/2/e38485 |
| _version_ | 1797734771008208896 |
|---|---|
| author | Niko Yiannakoulias J Connor Darlington Catherine E Slavik Grant Benjamin |
| author_facet | Niko Yiannakoulias J Connor Darlington Catherine E Slavik Grant Benjamin |
| author_sort | Niko Yiannakoulias |
| collection | DOAJ |
| description |
BackgroundSocial media platforms, such as Facebook, Instagram, Twitter, and YouTube, have a role in spreading anti-vaccine opinion and misinformation. Vaccines have been an important component of managing the COVID-19 pandemic, so content that discourages vaccination is generally seen as a concern to public health. However, not all negative information about vaccines is explicitly anti-vaccine, and some of it may be an important part of open communication between public health experts and the community.
ObjectiveThis research aimed to determine the frequency of negative COVID-19 vaccine information on Twitter in the first 4 months of 2021.
MethodsWe manually coded 7306 tweets sampled from a large sampling frame of tweets related to COVID-19 and vaccination collected in early 2021. We also coded the geographic location and mentions of specific vaccine producers. We compared the prevalence of anti-vaccine and negative vaccine information over time by author type, geography (United States, United Kingdom, and Canada), and vaccine developer.
ResultsWe found that 1.8% (131/7306) of tweets were anti-vaccine, but 21% (1533/7306) contained negative vaccine information. The media and government were common sources of negative vaccine information but not anti-vaccine content. Twitter users from the United States generated the plurality of negative vaccine information; however, Twitter users in the United Kingdom were more likely to generate negative vaccine information. Negative vaccine information related to the Oxford/AstraZeneca vaccine was the most common, particularly in March and April 2021.
ConclusionsOverall, the volume of explicit anti-vaccine content on Twitter was small, but negative vaccine information was relatively common and authored by a breadth of Twitter users (including government, medical, and media sources). Negative vaccine information should be distinguished from anti-vaccine content, and its presence on social media could be promoted as evidence of an effective communication system that is honest about the potential negative effects of vaccines while promoting the overall health benefits. However, this content could still contribute to vaccine hesitancy if it is not properly contextualized. |
| first_indexed | 2024-03-12T12:49:18Z |
| format | Article |
| id | doaj.art-271fec42936446b09f1151dfb296128c |
| institution | Directory Open Access Journal |
| issn | 2564-1891 |
| language | English |
| last_indexed | 2024-03-12T12:49:18Z |
| publishDate | 2022-08-01 |
| publisher | JMIR Publications |
| record_format | Article |
| series | JMIR Infodemiology |
| spelling | doaj.art-271fec42936446b09f1151dfb296128c2023-08-28T22:58:04ZengJMIR PublicationsJMIR Infodemiology2564-18912022-08-0122e3848510.2196/38485Negative COVID-19 Vaccine Information on Twitter: Content AnalysisNiko Yiannakouliashttps://orcid.org/0000-0003-3443-1071J Connor Darlingtonhttps://orcid.org/0000-0002-4232-5714Catherine E Slavikhttps://orcid.org/0000-0002-3077-239XGrant Benjaminhttps://orcid.org/0000-0003-0744-9428 BackgroundSocial media platforms, such as Facebook, Instagram, Twitter, and YouTube, have a role in spreading anti-vaccine opinion and misinformation. Vaccines have been an important component of managing the COVID-19 pandemic, so content that discourages vaccination is generally seen as a concern to public health. However, not all negative information about vaccines is explicitly anti-vaccine, and some of it may be an important part of open communication between public health experts and the community. ObjectiveThis research aimed to determine the frequency of negative COVID-19 vaccine information on Twitter in the first 4 months of 2021. MethodsWe manually coded 7306 tweets sampled from a large sampling frame of tweets related to COVID-19 and vaccination collected in early 2021. We also coded the geographic location and mentions of specific vaccine producers. We compared the prevalence of anti-vaccine and negative vaccine information over time by author type, geography (United States, United Kingdom, and Canada), and vaccine developer. ResultsWe found that 1.8% (131/7306) of tweets were anti-vaccine, but 21% (1533/7306) contained negative vaccine information. The media and government were common sources of negative vaccine information but not anti-vaccine content. Twitter users from the United States generated the plurality of negative vaccine information; however, Twitter users in the United Kingdom were more likely to generate negative vaccine information. Negative vaccine information related to the Oxford/AstraZeneca vaccine was the most common, particularly in March and April 2021. ConclusionsOverall, the volume of explicit anti-vaccine content on Twitter was small, but negative vaccine information was relatively common and authored by a breadth of Twitter users (including government, medical, and media sources). Negative vaccine information should be distinguished from anti-vaccine content, and its presence on social media could be promoted as evidence of an effective communication system that is honest about the potential negative effects of vaccines while promoting the overall health benefits. However, this content could still contribute to vaccine hesitancy if it is not properly contextualized.https://infodemiology.jmir.org/2022/2/e38485 |
| spellingShingle | Niko Yiannakoulias J Connor Darlington Catherine E Slavik Grant Benjamin Negative COVID-19 Vaccine Information on Twitter: Content Analysis JMIR Infodemiology |
| title | Negative COVID-19 Vaccine Information on Twitter: Content Analysis |
| title_full | Negative COVID-19 Vaccine Information on Twitter: Content Analysis |
| title_fullStr | Negative COVID-19 Vaccine Information on Twitter: Content Analysis |
| title_full_unstemmed | Negative COVID-19 Vaccine Information on Twitter: Content Analysis |
| title_short | Negative COVID-19 Vaccine Information on Twitter: Content Analysis |
| title_sort | negative covid 19 vaccine information on twitter content analysis |
| url | https://infodemiology.jmir.org/2022/2/e38485 |
| work_keys_str_mv | AT nikoyiannakoulias negativecovid19vaccineinformationontwittercontentanalysis AT jconnordarlington negativecovid19vaccineinformationontwittercontentanalysis AT catherineeslavik negativecovid19vaccineinformationontwittercontentanalysis AT grantbenjamin negativecovid19vaccineinformationontwittercontentanalysis |