EXIST 2022: Sexism categorisation

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) and, if so, to categorize the message according to the type of sexism (according to the categorization proposed by experts and that takes into account the different facets of women that are undermined): (i) ideological and inequality, (ii) stereotyping and dominance, (iii) objectification, (iv) sexual violence, and (v) misogyny and non-sexual violence.

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
NLP topic
Abstract task
Dataset
Year
2022
Ranking metric
Macro F1

Task results

System MacroPrecision MacroRecall MacroF1 Sort ascending
task2 ELiRF-VRAIN 3.tsv es 0.5891 0.4881 0.4867
task2 avacaondata 1.tsv es 0.5718 0.5169 0.4864
task2 UMU 1 es 0.5985 0.5026 0.4855
task2 ELiRF-VRAIN 1.tsv es 0.5818 0.4964 0.4841
task2 AIT FHSTP 3.tsv es 0.5416 0.5215 0.4775

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.