| Título |
Impact of Text Preprocessing and Feature Selection on Hate Speech Detection in Online Messages Towards the LGBTQ+ Community in Mexico |
| Tipo |
Congreso |
| Sub-tipo |
Memoria |
| Descripción |
2023 Iberian Languages Evaluation Forum, IberLEF 2023 |
| Resumen |
The prevalence of online hate speech targeting the LGBTQ+ community poses a significant challenge in maintaining a safe and inclusive digital environment. This paper deals with the importance of addressing this issue by proposing methods for detecting this offensive messages towards this community population in Mexican Spanish. The study explores a considerable variety of approaches to solve the task with classical machine learning algorithms and with different approaches for feature extraction. Additionally, text preprocessing techniques specific to Twitter data, and word embeddings are employed to enhance the performance of the models. Through experimentation and comparative analysis, we assess the effectiveness of these methods in identifying and classifying offensive messages. The findings of this research contribute to the development of robust tools for identifying and mitigating online hate speech, ultimately fostering a more inclusive and tolerant digital space for the LGBTQ+ community. © 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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