SemEval-2022 Task 5: Multimedia Automatic Misogyny Identification

no code implementations • SemEval (NAACL) 2022 • Elisabetta Fersini, Francesca Gasparini, Giulia Rizzi, Aurora Saibene, Berta Chulvi, Paolo Rosso, Alyssa Lees, Jeffrey Sorensen

The paper describes the SemEval-2022 Task 5: Multimedia Automatic Misogyny Identification (MAMI), which explores the detection of misogynous memes on the web by taking advantage of available texts and images.

AI-UPV at EXIST 2023 -- Sexism Characterization Using Large Language Models Under The Learning with Disagreements Regime

1 code implementation • 7 Jul 2023 • Angel Felipe Magnossão de Paula, Giulia Rizzi, Elisabetta Fersini, Damiano Spina

In particular, our system is articulated in three different pipelines.

Task 2

Benchmark dataset of memes with text transcriptions for automatic detection of multi-modal misogynistic content

1 code implementation • 15 Jun 2021 • Francesca Gasparini, Giulia Rizzi, Aurora Saibene, Elisabetta Fersini

Two further binary labels have been collected from both the experts and the crowdsourcing platform, for memes evaluated as misogynistic, concerning aggressiveness and irony.