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Abstract
The Internet serves as a dynamic and expansive space where numerous groups seek to exchange and disseminate their views. Some of those groups aim to promote hateful ideologies, bigotry, conspiracy theories while externalizing their anger. To achieve this, a spectrum of online platforms is utilized, ranging from mainstream social networks to underground forums. Notably, imageboards stand out as fertile ground where these ideologies flourish, due to anonymity, community engagement, and a plethora of hateful content. This study endeavors to examine the prevalence of bigotry in these spaces within the Brazilian context. Natural language processing algorithms provide the possibility to explore discursive features of massive text sets, extracting latent information and patterns in a relatively simple and automated way. This study shows how prejudice forms the basis of the different discourses found in Brazilian imageboards. Notably, these discourses not only echo historically rooted hateful ideologies but also assimilate conspiratorial perspectives and instances of bigotry emanating from non-Brazilian imageboards.
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