Odio-BERT: Evaluating domain task impact in hate speech detection

Article type: Research Article

Authors: Yigezu, Mesay Gemeda | Kolesnikova, Olga^{; *} | Gelbukh, Alexander | Sidorov, Grigori

Affiliations: Centro de Investigación en Computación(CIC), Instituto Politécnico Nacional (IPN), Mexico City, Mexico

Correspondence: [*] Corresponding author. Olga Kolesnikova. E-mail: mgemedak2022@cic.ipn.mx.

Abstract: The rise of social media and micro-blogging platforms has led to concerns about hate speech, its potential to incite violence, psychological trauma, extremist beliefs, and self-harm. We have proposed a novel model, Odio-BERT for detecting hate speech using a pretrained BERT language model. This specialized model is specifically designed for detecting hate speech in the Spanish language, and when compared to existing models, it consistently outperforms them. The study provides valuable insights into addressing hate speech in the Spanish language and explores the impact of domain tasks.

Keywords: BERT, hate speech, domain task, fine tune, Odio-BERT, Spanish

DOI: 10.3233/JIFS-219349

Journal: Journal of Intelligent & Fuzzy Systems, vol. Pre-press, no. Pre-press, pp. 1-12, 2024