Hate Speech Detection in Portuguese Using BERTimbau

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MetadadosDescriçãoIdioma
Autor(es): dc.contributorUniversidade Estadual Paulista (UNESP)-
Autor(es): dc.creatorFrediani, João Otávio Rodrigues Ferreira-
Autor(es): dc.creatorGarcia, Gabriel Lino-
Autor(es): dc.creatorPaiola, Pedro Henrique-
Autor(es): dc.creatorPassos, Leandro Aparecido-
Autor(es): dc.creatorPapa, João Paulo-
Autor(es): dc.creatorMarana, Aparecido Nilceu-
Data de aceite: dc.date.accessioned2025-08-21T18:16:17Z-
Data de disponibilização: dc.date.available2025-08-21T18:16:17Z-
Data de envio: dc.date.issued2025-04-29-
Data de envio: dc.date.issued2024-12-31-
Fonte completa do material: dc.identifierhttp://dx.doi.org/10.1007/978-3-031-76607-7_18-
Fonte completa do material: dc.identifierhttps://hdl.handle.net/11449/298909-
Fonte: dc.identifier.urihttp://educapes.capes.gov.br/handle/11449/298909-
Descrição: dc.descriptionHate speech refers to language expressions that attack individuals or groups based on specific characteristics associated with their identities, causing lasting damage. Social networks have become a pertinent environment for hate speech proliferation since they allow anonymity and maintain a safe distance from aggressors and assaulted victims. With the amount of data published every minute, automatic identification of hate speech using machine learning gathered much attention from academic and industrial researchers. However, as with many natural language processing tasks, the efforts mainly focused on English, and languages like Portuguese remain less explored. Therefore, this paper aims to experiment with different techniques to deal with the challenges associated with low-resource languages in automatic hate speech detection. It evaluates whether knowledge transferred from offensive speech detection as a source task can be effective for hate detection and if the unbalanced data poses an obstacle for a Portuguese pre-trained BERT model, BERTimbau. Experimental results show that transferring learning between tasks does not improve performance and that using balanced data leads to better F1 scores and Cohen’s Kappa.-
Descrição: dc.descriptionSchool of Sciences São Paulo State University (UNESP)-
Descrição: dc.descriptionSchool of Sciences São Paulo State University (UNESP)-
Formato: dc.format244-255-
Idioma: dc.languageen-
Relação: dc.relationLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)-
???dc.source???: dc.sourceScopus-
Palavras-chave: dc.subjectHate Speech-
Palavras-chave: dc.subjectMachine Learning-
Palavras-chave: dc.subjectNatural Language Processing-
Palavras-chave: dc.subjectPortuguese Language-
Palavras-chave: dc.subjectUndersampling-
Título: dc.titleHate Speech Detection in Portuguese Using BERTimbau-
Tipo de arquivo: dc.typeaula digital-
Aparece nas coleções:Repositório Institucional - Unesp

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