CoVaxxy: A Collection of English-language Twitter Posts About COVID-19 Vaccines
Matthew R. DeVerna, Francesco Pierri, Bao Tran Truong, John, Bollenbacher, David Axelrod, Niklas Loynes, Christopher Torres-Lugo,, Kai-Cheng Yang, Filippo Menczer, and John Bryden

TL;DR
The paper introduces CoVaxxy, a comprehensive Twitter dataset on COVID-19 vaccines, along with a visualization dashboard, to facilitate research on misinformation and vaccine adoption patterns.
Contribution
It provides a new dataset and visualization tools for analyzing COVID-19 vaccine-related social media content and misinformation.
Findings
Analysis of tweet volume and hashtags over time
Prevalence of high- and low-credibility sources
Geographical distribution of vaccine-related posts
Abstract
With a substantial proportion of the population currently hesitant to take the COVID-19 vaccine, it is important that people have access to accurate information. However, there is a large amount of low-credibility information about vaccines spreading on social media. In this paper, we present the CoVaxxy dataset, a growing collection of English-language Twitter posts about COVID-19 vaccines. Using one week of data, we provide statistics regarding the numbers of tweets over time, the hashtags used, and the websites shared. We also illustrate how these data might be utilized by performing an analysis of the prevalence over time of high- and low-credibility sources, topic groups of hashtags, and geographical distributions. Additionally, we develop and present the CoVaxxy dashboard, allowing people to visualize the relationship between COVID-19 vaccine adoption and U.S. geo-located posts in…
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Taxonomy
TopicsMisinformation and Its Impacts · Vaccine Coverage and Hesitancy · Data-Driven Disease Surveillance
