This is a multi-class classification tasks. The systems have to decide whether or not a given tweet contains sexist expressions or behaviours (i.e., it is sexist itself, describes a sexist situation or criticizes a sexist behaviour).
Publication
Francisco Rodríguez-Sánchez, Jorge Carrillo-de-Albornoz, Laura Plaza, Julio Gonzalo, Paolo Rosso, Miriam Comet, Trinidad Donoso. Overview of EXIST 2021: sEXism Identification in Social neTworks.. Procesamiento del Lenguaje Natural, Vol 67, septiembre 2021.
Competition
Language
Spanish
English
URL Task
NLP topic
Abstract task
Dataset
Year
2021
Publication link
Ranking metric
Accuracy
Task results
| System | Precision | Recall | F1 | CEM | Accuracy Sort ascending | MacroPrecision | MacroRecall | MacroF1 | RMSE | MicroPrecision | MicroRecall | MicroF1 | MAE | MAP | UAS | LAS | MLAS | BLEX | Pearson correlation | Spearman correlation | MeasureC | BERTScore | EMR | Exact Match | F0.5 | Hierarchical F | ICM | MeasureC | Propensity F | Reliability | Sensitivity | Sentiment Graph F1 | WAC | b2 | erde30 | sent | weighted f1 |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| AI_UPV_1 | 0.7804 | 0.7801 | 0.7806 | 0.7802 | |||||||||||||||||||||||||||||||||
| SINAI_TL_1 | 0.7800 | 0.7796 | 0.7800 | 0.7797 | |||||||||||||||||||||||||||||||||
| AIT_FHSTP_2 | 0.7754 | 0.7751 | 0.7756 | 0.7752 | |||||||||||||||||||||||||||||||||
| multiaztertest_1 | 0.7740 | 0.7741 | 0.7727 | 0.7731 | |||||||||||||||||||||||||||||||||
| nlp_unes_team_1 | 0.7720 | 0.7720 | 0.7737 | 0.7696 |
