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Anti-vaccine content or negative vaccine information? Patterns of Twitter content about Covid-19 vaccines (Preprint)

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.

Authors

Yiannakoulias N; Darlington JC; Slavik CE; Benjamin G

Publication date

April 4, 2022

DOI

10.2196/preprints.38485

Preprint server

JMIR Preprints
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