This task aims to classify sexist tweets based on the author's intent, helping to understand the role social media plays in the emission and dissemination of sexist messages. In this task, a ternary classification is proposed: direct, reported, judgemental. This task includes a soft-soft evaluation, where the probability of each label predicted by the system is compared with the probability defined based on the annotation disagreement in the gold standard.
Publication
Plaza, L. et al. (2024).EXIST 2024: sEXism Identification in Social neTworks and Memes. Experimental IR Meets Multilinguality, Multimodality, and Interaction. CLEF 2024. Lecture Notes in Computer Science, volume 14612
Language
Spanish
English
URL Task
NLP topic
Dataset
Year
2024
Publication link
Ranking metric
ICMSoft
Task results
| System | ICM Soft Sort ascending |
|---|---|
| NYCU-NLP_2 | -0.2543 |
| NYCU-NLP_1 | -0.4059 |
| NYCU-NLP_3 | -0.5226 |
| BAZI_1 | -1.3468 |
| Victor-UNED_2 | -1.6440 |

