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

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 facilitate the development of policies to fight 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 hard-hard evaluation, where the labels predicted by the system are compared with the labels from 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
ICM

Task results

System ICM Sort ascending ICM Soft
DiTana-PV_1 -0.6996
DiTana-PV_2 -0.8450
MMICI_1 -0.9863
ROCurve_1 -1.0089
ROCurve_2 -1.1075 -0.2925

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.