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.

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