SemEval-2022 Task 5: Multimedia Automatic Misogyny Identification

Elisabetta Fersini, Francesca Gasparini, Giulia Rizzi, Aurora Saibene, Berta Chulvi, Paolo Rosso, Alyssa Lees, Jeffrey Sorensen


Abstract
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. The task has been organised in two related sub-tasks: the first one is focused on recognising whether a meme is misogynous or not (Sub-task A), while the second one is devoted to recognising types of misogyny (Sub-task B). MAMI has been one of the most popular tasks at SemEval-2022 with more than 400 participants, 65 teams involved in Sub-task A and 41 in Sub-task B from 13 countries. The MAMI challenge received 4214 submitted runs (of which 166 uploaded on the leader-board), denoting an enthusiastic participation for the proposed problem.The collection and annotation is described for the task dataset.The paper provides an overview of the systems proposed for the challenge, reports the results achieved in both sub-tasks and outlines a description of the main errors for a comprehension of the systems capabilities and for detailing future research perspectives.
Anthology ID:
2022.semeval-1.74
Volume:
Proceedings of the 16th International Workshop on Semantic Evaluation (SemEval-2022)
Month:
July
Year:
2022
Address:
Seattle, United States
Venue:
SemEval
SIGs:
SIGLEX | SIGSEM
Publisher:
Association for Computational Linguistics
Note:
Pages:
533–549
Language:
URL:
https://aclanthology.org/2022.semeval-1.74
DOI:
10.18653/v1/2022.semeval-1.74
Bibkey:
Cite (ACL):
Elisabetta Fersini, Francesca Gasparini, Giulia Rizzi, Aurora Saibene, Berta Chulvi, Paolo Rosso, Alyssa Lees, and Jeffrey Sorensen. 2022. SemEval-2022 Task 5: Multimedia Automatic Misogyny Identification. In Proceedings of the 16th International Workshop on Semantic Evaluation (SemEval-2022), pages 533–549, Seattle, United States. Association for Computational Linguistics.
Cite (Informal):
SemEval-2022 Task 5: Multimedia Automatic Misogyny Identification (Fersini et al., SemEval 2022)
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