Accepted for/Published in: JMIR Infodemiology
Date Submitted: Apr 4, 2022
Date Accepted: Aug 18, 2022
Negative Covid-19 vaccine information on Twitter
ABSTRACT
Background:
Evidence has suggested that major social media platforms, such Facebook, Instagram, Twitter and YouTube have a role in spreading anti-vaccine opinion and misinformation in recent years. Vaccines are seen as an important part of managing the Covid-19 pandemic, so barriers to vaccination are an important barrier to public health.
Objective:
The purpose of this research was to describe patterns in prevalence of anti-vaccine and negative vaccine information associated with Covid-19 on Twitter in the first four months of 2021.
Methods:
We manually coded 7306 Tweets sampled from a large frame of Tweets related to Covid-19 and vaccination collected between December 2020 and April 2021. We also coded geographic location and mentions of specific vaccine producersv
Results:
We found that less than 2% of Tweets were anti-vaccine but 21% contained negative vaccine information. The media and government are common sources of negative vaccine information, but not anti-vaccine content. Twitter users from the US generate the plurality of negative vaccine information, however Twitter users in the UK are more likely to generate negative vaccine information. Negative vaccine information related to the Oxford/AstraZeneca vaccine was most common, particularly in March and April of 2021.
Conclusions:
Overall, the volume of explicit anti-vaccine content on Twitter is small. On the other hand, negative vaccine information is relatively common, and is authored by a breadth of Twitter users (including government, medical and media sources) that communicate facts about vaccines. 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 negatives of vaccines while promoting the overall health benefits.
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Copyright
© The authors. All rights reserved. This is a privileged document currently under peer-review/community review (or an accepted/rejected manuscript). Authors have provided JMIR Publications with an exclusive license to publish this preprint on it's website for review and ahead-of-print citation purposes only. While the final peer-reviewed paper may be licensed under a cc-by license on publication, at this stage authors and publisher expressively prohibit redistribution of this draft paper other than for review purposes.