Overview of HOMO-MEX at Iberlef 2023: Hate speech detection in Online Messages directed Towards the MEXican Spanish speaking LGBTQ+ population

Gemma Bel-Enguix, Helena Gómez-Adorno, Gerardo Sierra, Juan Vásquez, Scott Thomas Andersen, Sergio Ojeda-Trueba


The detection of hate speech and stereotypes in online platforms has gained significant attention in the field of Natural Language Processing (NLP). Among various forms of discrimination, LGBTQ+ phobia is prevalent on social media, particularly on platforms like Twitter. The objective of the HOMO-MEX task is to encourage the development of NLP systems that can detect and classify LGBTQ+ phobic content in Spanish tweets, regardless of whether it is expressed aggressively or subtly. The task aims to address the lack of dedicated resources for LGBTQ+ phobia detection in Spanish Twitter and encourages participants to employ multi-label classification approaches.

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