Brazilian Social Media Anti-vaccine Information Disorder Dataset -- Telegram (2020-2025)
career value
196K/year
🤖 AI Summary
This study addresses the persistent decline in vaccination rates in Brazil, attributing it significantly to the spread of anti-vaccine misinformation on social media. To investigate this phenomenon, the authors present the first publicly available, high-quality dataset comprising approximately 4 million messages from 119 prominent Brazilian anti-vaccine Telegram channels, spanning 2020 to 2025. The dataset includes textual content, metadata, media attachments, and vaccine-related classification labels. Developed under a rigorous ethical and privacy-preserving framework, the project integrates advanced techniques for data collection, annotation, metadata extraction, and content categorization, thereby filling a critical gap in accessible and reproducible research on anti-vaccine discourse on Telegram. This open resource provides a foundational empirical basis for public health and computational social science research, supporting the design of targeted interventions and strategies to rebuild public trust in vaccines.
Application Category
📝 Abstract
Over the past decade, Brazil has experienced a decline in vaccination coverage, reversing decades of public health progress achieved through the National Immunization Program (PNI). Growing evidence points to the widespread circulation of vaccine-related misinformation -- particularly on social media platforms -- as a key factor driving this decline. Among these platforms, Telegram remains the only major platform permitting accessible and ethical data collection, offering insight into public channels where vaccine misinformation circulates extensively. This data paper introduces a curated dataset of about four million Telegram posts collected from 119 prominent Brazilian anti-vaccine channels between 2020 and 2025. The dataset includes message content, metadata, associated media, and classification related to vaccine posts, enabling researchers to examine how false or misleading information spreads, evolves, and influences public sentiment. By providing this resource, our aim is to support the scientific and public health community in developing evidence-based strategies to counter misinformation, promote trust in vaccination, and engage compassionately with individuals and communities affected by false narratives. The dataset and documentation are openly available for non-commercial research, under strict ethical and privacy guidelines at https://doi.org/10.25824/redu/5JIVDT
Problem
Research questions and friction points this paper is trying to address.
vaccine misinformation
social media
vaccination coverage
public health
anti-vaccine
Innovation
Methods, ideas, or system contributions that make the work stand out.
misinformation dataset
Telegram
vaccine hesitancy
social media analysis
public health communication
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