Abstract
This paper presents our submission to task 5 (Multimedia Automatic Misogyny Identification) of the SemEval 2022 competition. The purpose of the task is to identify given memes as misogynistic or not and further label the type of misogyny involved. In this paper, we present our approach based on language processing tools. We embed meme texts using GloVe embeddings and classify misogyny using BERT model. Our model obtains an F1-score of 66.24% and 63.5% in misogyny classification and misogyny labels, respectively.
Cite
CITATION STYLE
Sharma, G., Gitte, G. S., Goyal, S., & Sharma, R. (2022). IITR CodeBusters at SemEval-2022 Task 5: Misogyny Identification using Transformers. In SemEval 2022 - 16th International Workshop on Semantic Evaluation, Proceedings of the Workshop (pp. 728–732). Association for Computational Linguistics (ACL). https://doi.org/10.18653/v1/2022.semeval-1.100
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