2021/01/19 by Matthew DeVerna, DeVerna, Matthew R., Francesco Pierri +18
Medicine · Social Sciences · #Data-Driven Disease Surveillance #FOS: Computer and information sciences #Misinformation and Its Impacts #Social and Information Networks (cs.SI) #Vaccine Coverage and Hesitancy
paper · pdf · doi:10.48550/arxiv.2101.07694
openalex publication_date 2021/01/19 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/28
With a substantial proportion of the population currently hesitant to take\nthe COVID-19 vaccine, it is important that people have access to accurate\ninformation. However, there is a large amount of low-credibility information\nabout vaccines spreading on social media. In this paper, we present the CoVaxxy\ndataset, a growing collection of English-language Twitter posts about COVID-19\nvaccines. Using one week of data, we provide statistics regarding the numbers\nof tweets over time, the hashtags used, and the websites shared. We also\nillustrate how these data might be utilized by performing an analysis of the\nprevalence over time of high- and low-credibility sources, topic groups of\nhashtags, and geographical distributions. Additionally, we develop and present\nthe CoVaxxy dashboard, allowing people to visualize the relationship between\nCOVID-19 vaccine adoption and U.S. geo-located posts in our dataset. This\ndataset can be used to study the impact of online information on COVID-19\nhealth outcomes (e.g., vaccine uptake) and our dashboard can help with\nexploration of the data.\n