Binary classification problem, consisting in determmine whether a text or message is sexist or not. It includes any type of sexist expression or related phenomena, like descriptive or reported assertions where the sexist message is a report or a description of a sexist event. In particular, we consider two labels:
- Sexist: the tweet or gab expresses sexist behaviours or discourses.
- Non-Sexist: the tweet or gab does not express any sexist behaviour or discourse.
Publication
Francisco Rodríguez-Sánchez, Jorge Carrillo-de-Albornoz, Laura Plaza, Adrián Mendieta-Aragón, Guillermo Marco-Remón, Maryna Makeienko, María Plaza, Julio Gonzalo, Damiano Spina, Paolo Rosso (2022) Overview of EXIST 2022: sEXism Identification in Social neTworks. Procesamiento del Lenguaje Natural, Revista nº 69, septiembre de 2022, pp. 229-240.
Language
Spanish
URL Task
NLP topic
Abstract task
Dataset
Year
2022
Publication link
Ranking metric
Accuracy
Task results
| System | Accuracy |
|---|---|
| ixambert-base-cased | 0.7100 |
| bert-base-spanish-wwm-cased | 0.7200 |
| distillbert-base-spanish-uncased | 0.7200 |
| distilbert-base-multilingual-cased | 0.7200 |
| bert-base-multilingual-cased | 0.7200 |
| bertin-roberta-base-spanish | 0.7300 |
| PlanTL-GOB-ES-roberta-base-bne | 0.7400 |
| xlm-roberta-base | 0.7400 |
| PlanTL-GOB-ES-roberta-large-bne | 0.7500 |
| xlm-roberta-large | 0.7700 |
