Background False claims about COVID-19 vaccines can undermine public trust in ongoing vaccination campaigns, posing a threat to global public health. Misinformation originating from various sources has been spreading on the web since the beginning of the COVID-19 pandemic. Antivaccine activists have also begun to use platforms such as Twitter to promote their views. To properly understand the phenomenon of vaccine hesitancy through the lens of social media, it is of great importance to gather the relevant data. Objective In this paper, we describe a data set of Twitter posts and Twitter accounts that publicly exhibit a strong antivaccine stance. The data set is made available to the research community via our AvaxTweets data set GitHub repository. We characterize the collected accounts in terms of prominent hashtags, shared news sources, and most likely political leaning. Methods We started the ongoing data collection on October 18, 2020, leveraging the Twitter streaming application programming interface (API) to follow a set of specific antivaccine-related keywords. Then, we collected the historical tweets of the set of accounts that engaged in spreading antivaccination narratives between October 2020 and December 2020, leveraging the Academic Track Twitter API. The political leaning of the accounts was estimated by measuring the political bias of the media outlets they shared. Results We gathered two curated Twitter data collections and made them publicly available: (1) a streaming keyword–centered data collection with more than 1.8 million tweets, and (2) a historical account–level data collection with more than 135 million tweets. The accounts engaged in the antivaccination narratives lean to the right (conservative) direction of the political spectrum. The vaccine hesitancy is fueled by misinformation originating from websites with already questionable credibility. Conclusions The vaccine-related misinformation on social media may exacerbate the levels of vaccine hesitancy, hampering progress toward vaccine-induced herd immunity, and could potentially increase the number of infections related to new COVID-19 variants. For these reasons, understanding vaccine hesitancy through the lens of social media is of paramount importance. Because data access is the first obstacle to attain this goal, we published a data set that can be used in studying antivaccine misinformation on social media and enable a better understanding of vaccine hesitancy.

BACKGROUND False claims about COVID-19 vaccines can undermine public trust in ongoing vaccination campaigns, thus posing a threat to global public health. Misinformation originating from various sources has been spreading online since the beginning of the COVID-19 pandemic. Anti-vaccine activists have also begun to utilize platforms like Twitter to share their views. To properly understand the phenomenon of vaccine hesitancy through the lens of online social media, it is of greatest importance to gather the relevant data. OBJECTIVE In this paper, we describe a dataset of Twitter posts that exhibit a strong anti-vaccine stance. The dataset is made available to the research community via our AvaxTweets dataset GitHub repository. METHODS We started the ongoing data collection on October 18, 2020, leveraging the Twitter streaming application programming interface (API) to follow a set of specific anti-vaccine related keywords. Additionally, we collect the historical tweets of the set of accounts that engaged in spreading anti-vaccination narratives at some point during 2020. RESULTS Since the inception of our collection, we have published two collections: a) a streaming keyword-centered data collection with more than 1.8 million tweets, and b) a historical account-level collection with more than 135 million tweets. In this paper we present descriptive analyses showing the volume of activity over time, geographical distributions, topics, news sources, and inferred accounts’ political leaning. CONCLUSIONS The vaccine-related misinformation on social media may exacerbate the levels of vaccine hesitancy, hampering the progress toward vaccine-induced herd immunity, and potentially increase infections related to new COVID-19 variants. For these reasons, understanding vaccine hesitancy through the lens of social media is of paramount importance. Since data access is the first obstacle to attain that, we publish the dataset that can be used in studying anti-vaccine misinformation on social media and enable a better understanding of vaccine hesitancy.