COVID-19 Vaccine Hesitancy on Social Media: Building a Public Twitter Dataset of Anti-vaccine Content, Vaccine Misinformation and Conspiracies

TL;DR

This paper introduces a comprehensive Twitter dataset of over 137 million tweets related to COVID-19 vaccine misinformation and anti-vaccine content, facilitating research on vaccine hesitancy and misinformation spread.

Contribution

The paper provides the first large-scale, publicly available Twitter dataset focused on anti-vaccine content, including both real-time and historical data, with detailed descriptive analyses.

Findings

High volume of anti-vaccine tweets over time

Geographical distribution of misinformation spread

Identified political leanings of spreading accounts

Abstract

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. In this paper, we present a dataset of Twitter posts that exhibit a strong anti-vaccine stance. The dataset consists of two parts: 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. The former leverages the Twitter streaming API to follow a set of specific vaccine-related keywords starting from mid-October 2020. The latter consists of all historical tweets of 70K accounts that were engaged in the active spreading of anti-vaccine narratives. We present descriptive analyses showing the volume of activity over time, geographical distributions, topics, news sources, and inferred account political leaning. This dataset can be used in studying anti-vaccine misinformation on social media and enable a better understanding of vaccine hesitancy. In compliance with Twitter's Terms of Service, our anonymized dataset is publicly available at: https://github.com/gmuric/avax-tweets-dataset