| Resumen |
We present the HOMO-MEX shared task organized at IberLEF 2024, as part of the 40th. International Conference of the Spanish Society for Natural Language Processing (SEPLN 2024). The aim of this task is to promote the development of natural language processing systems capable of detecting and classifying LGBT+phobic content in Mexican-Spanish digital posts and song lyrics. HOMO-MEX 2024 is composed of three subtasks: Task 1 on LGBT+phobia detection on social media posts, Task 2 on fine-grained phobia identification, and Task 3 on LGBT+phobia detection on song lyrics. In this second edition of HOMO-MEX, 40 participants registered on our Codabench platform. Subtask 1 received 19 submissions, subtask 2 received 10 submissions, and Subtask 3 got 17 submissions. Finally, 11 teams presented papers describing their systems. Most systems used transformer-based approaches to tackle the task, while the best-performing teams included data augmentation and preprocessing techniques. © 2024 Sociedad Española para el Procesamiento del Lenguaje Natural. |
