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Other literature type . 2025
License: CC BY
Data sources: ZENODO
ZENODO
Other literature type . 2025
License: CC BY
Data sources: Datacite
ZENODO
Other literature type . 2025
License: CC BY
Data sources: Datacite
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Anti-vaccine Disinformation in Latin America and the Caribbean: Mapping 175 Alleged Harms and 80 False Antidotes in Conspiracy Theory Communities on Telegram

Authors: Silva, Ergon Cugler de Moraes; Ricard, Julie C.; Alves, Mario Aquino; Rocha, Gabriel; Vitória, Stefanny;

Anti-vaccine Disinformation in Latin America and the Caribbean: Mapping 175 Alleged Harms and 80 False Antidotes in Conspiracy Theory Communities on Telegram

Abstract

A desinformação sobre vacinas é reconhecida como um desafio crítico de saúde pública. Apesar das evidências crescentes que associam desinformação e hesitação vacinal, ainda carecemos de um panorama abrangente das narrativas antivacina que circulam pela América Latina e pelo Caribe. Assim, a pergunta que orienta este estudo é: Quais as principais narrativas relacionadas à vacinas em comunidades de teorias da conspiração do Telegram na América Latina e o Caribe?. Nosso desenho de pesquisa examina 1.785 comunidades abertas de teorias da conspiração no Telegram na região (2016-2025), abrangendo 5,8 milhões de usuários ativos e 81 milhões de postagens. Analisamos um corpus de conteúdo relacionado a vacinas por meio de métodos mistos, incluindo mineração computacional de texto, codificação de conteúdo com reconhecimento de rede e análise qualitativa. Constatamos que o conteúdo antivacina em comunidades conspiratórias disparou após a Pandemia, crescendo 689,4 vezes entre 2019 e 2021. Mapeamos 175 supostos danos, que variam de morte súbita e alteração do DNA a envenenamento e câncer, e 80 falsos antídotos que exploram a pseudociência e a espiritualidade. Cada suposto dano é associado a um “antídoto” comercializável. As alegações antivacina em comunidades conspiratórias funcionam como funis de conversão: atraem pelo medo e, em seguida, vendem produtos, cursos e terapias como “soluções”.

Vaccine disinformation is acknowledged as a critical public-health challenge. Despite growing evidence associating disinformation and vaccine hesitancy, we lack a comprehensive panorama of the anti-vaccine narratives circulating across Latin America and the Caribbean. As such, the question guiding this study is: What are the main vaccine-related narratives in conspiracy-theory communities on Telegram in Latin America and the Caribbean? Our research design examines 1,785 open Telegram conspiracy communities across the region (2016-2025), comprising 5.8 million active users and 81 million posts. We analyze a corpus of vaccine-related content using mixed-methods, including computational text mining, network-aware content coding, and qualitative analysis. We find that anti-vaccine content in conspiracy-theory communities surged after the pandemic, growing by 689.4 times from 2019 to 2021. We map 175 alleged harms, ranging from sudden death and DNA alteration to poisoning and cancer, and 80 false antidotes that leverage pseudoscience and spirituality. Each alleged harm is paired with a marketable “antidote”. Anti-vaccine claims in conspiracy communities are found to function as conversion funnels: they attract through fear and then sell products, courses, and therapies as “solutions”.

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
0
Average
Average
Average
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