| Título |
LIDOMA at HOMO-MEX2023@IberLEF: Hate Speech Detection Towards the Mexican Spanish-Speaking LGBT+ Population. The Importance of Preprocessing Before Using BERT-Based Models |
| Tipo |
Congreso |
| Sub-tipo |
Memoria |
| Descripción |
2023 Iberian Languages Evaluation Forum, IberLEF 2023 |
| Resumen |
Hate speech targeting LGBT+ individuals poses a deeply ingrained problem with wide-ranging consequences, encompassing substance abuse disorders and discrimination. These specific concerns are particularly amplified in Mexico. In this paper, we present our submission on the first track of the HOMO-MEX: Hate Speech Detection towards the Mexican Spanish-Speaking LGBT+ Population. We explore the dataset and we employ transformer architectures, who have demonstrated significant efficacy in similar sentiment analysis tasks. Specifically, we utilize BERT-based models and we show the importance of preprocessing by reaching the last place in the competition with a Macro F1 score of 0.73. The source code to reproduce our results can be found at https://github.com/moeintash72. © 2023 Copyright for this paper by its authors. Use permitted under Creative Commons License Attribution 4.0 International (CC BY 4.0). |
| Observaciones |
CEUR Workshop Proceedings, v. 3496 |
| Lugar |
Jaen |
| País |
España |
| No. de páginas |
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| Vol. / Cap. |
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| Inicio |
2023-09-26 |
| Fin |
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| ISBN/ISSN |
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