Abstract
Everyday more users are using memes on social media platforms to convey a message with text and image combined. Although there are many fun and harmless memes being created and posted, there are also ones that are hateful and offensive to particular groups of people. In this article present a novel approach based on the CLIP (Radford et al., 2021) network to detect misogynous memes and find out the types of misogyny in that meme. We participated in Task A and Task B of the Multimedia Automatic Misogyny Identification (MaMi) challenge (Fersini et al., 2022) and our best scores are 0.694 and 0.681 respectively.
Cite
CITATION STYLE
Behzadi, M., Derakhshan, A., & Harris, I. G. (2022). Mitra Behzadi at SemEval-2022 Task 5: Multimedia Automatic Misogyny Identification method based on CLIP. In SemEval 2022 - 16th International Workshop on Semantic Evaluation, Proceedings of the Workshop (pp. 724–727). Association for Computational Linguistics (ACL). https://doi.org/10.18653/v1/2022.semeval-1.99
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