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 Sort ascending |
|---|---|
| Hermes-3-Llama-3.1-8B_mix_6 | 0.8065 |
| Hermes-3-Llama-3.1-8B | 0.8065 |
| Hermes-3-Llama-3.1-8B_mix_4 | 0.8065 |
| Hermes-3-Llama-3.1-8B_2 | 0.8065 |
| Hermes-3-Llama-3.1-8B_mix_5 | 0.8065 |
| Qwen2.5-14B-Instruct | 0.8027 |
| Qwen2.5-14B-Instruct_mix | 0.8027 |
| Llama_3.1-8B-Instruct 0 shot no BIO v3 | 0.7989 |
| Llama_3.1-8B-Instruct 0 shot no BIO v4 | 0.7989 |
| Llama_3.1-8B-Instruct 0 shot no BIO v2 | 0.7989 |
