RoBEXedda: Sexism Detection in Tweets

Sexism remains a pervasive issue, significantly hindering women's progress in various aspects of life. This paper focuses on online misogyny, where women face high levels of abuse and threats. The “EXIST 2024” challenge aims to detect and classify sexist content on social media. In particular, in this paper, we address the “Sexism Categorization in Tweets” task, which involves identifying sexist tweets and categorizing them into predefined categories. A dataset comprising over 10,000 tweets in English and Spanish was exploited to train Transformer-based systems with “Binary Relevance” and “Classifier Chain” architectures. This report presents an analysis of the performance of our three candidate models in relation to the EXIST 2024 challenge. It includes a detailed examination of the results obtained and a comparison with the official ranking of the challenge. As team “Medusa”, we achieved second place in the competition, with three runs submitted in the soft-soft ranking. The models runs, designated “RoBEXedda”, attained the fourth, fifth, and sixth positions in the “Task 3 Soft-Soft ALL” ranking.