EXIST-2024: Sexism categorization in memes (soft-soft)

Many aspects of a woman's life can be the subject of sexist attitudes, such as domestic and parental roles, professional opportunities, sexual image, and life expectations, to name a few. Automatically detecting which of these aspects of women are most frequently attacked on social media will help in developing policies to combat sexism. In this task, each sexist meme must be classified into one or more of the following categories: IDEOLOGICAL AND INEQUALITY, STEREOTYPING AND DOMINANCE, OBJECTIFICATION, SEXUAL VIOLENCE, MISOGYNY AND NON-SEXUAL VIOLENCE. This task includes a soft-soft evaluation, where the predicted label probabilities from the system are compared with the probabilities defined based on the disagreement in the annotation 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
NLP topic
Dataset
Year
2024
Ranking metric
ICMSoft

Task results

If you have published a result better than those on the list, send a message to odesia-comunicacion@lsi.uned.es indicating the result and the DOI of the article, along with a copy of it if it is not published openly.