@inproceedings{h-etal-2024-quartet-lt,
title = "Quartet@{LT}-{EDI} 2024: A {SVM}-{R}es{N}et50 Approach For Multitask Meme Classification - Unraveling Misogynistic and Trolls in Online Memes",
author = "H, Shaun and
Sivakumar, Samyuktaa and
R, Rohan and
Jayaguptha, Nikilesh and
Thenmozhi, Durairaj",
editor = {Chakravarthi, Bharathi Raja and
B, Bharathi and
Buitelaar, Paul and
Durairaj, Thenmozhi and
Kov{\'a}cs, Gy{\"o}rgy and
Garc{\'\i}a Cumbreras, Miguel {\'A}ngel},
booktitle = "Proceedings of the Fourth Workshop on Language Technology for Equality, Diversity, Inclusion",
month = mar,
year = "2024",
address = "St. Julian's, Malta",
publisher = "Association for Computational Linguistics",
url = "https://aclanthology.org/2024.ltedi-1.27",
pages = "221--226",
abstract = "Meme is a very popular term prevailing among almost all social media platforms in recent days. A meme can be a combination of text and image whose sole purpose is meant to be funny and entertain people. Memes can sometimes promote misogynistic content expressing hatred, contempt, or prejudice against women. The Shared Task LT{--}EDI 2024: Multitask Meme Classification: Unraveling Misogynistic and Trolls in Online Memes Task 1 was created with the purpose to classify social media memes as {``}misogynistic{''} and {``}Non - Misogynistic{''}. The task encompassed Tamil and Malayalam datasets. We separately classified the textual data using Multinomial Naive Bayes and pictorial data using ResNet50 model. The results of from both data were combined to yield an overall result. We were ranked 2nd for both languages in this task.",
}
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<abstract>Meme is a very popular term prevailing among almost all social media platforms in recent days. A meme can be a combination of text and image whose sole purpose is meant to be funny and entertain people. Memes can sometimes promote misogynistic content expressing hatred, contempt, or prejudice against women. The Shared Task LT–EDI 2024: Multitask Meme Classification: Unraveling Misogynistic and Trolls in Online Memes Task 1 was created with the purpose to classify social media memes as “misogynistic” and “Non - Misogynistic”. The task encompassed Tamil and Malayalam datasets. We separately classified the textual data using Multinomial Naive Bayes and pictorial data using ResNet50 model. The results of from both data were combined to yield an overall result. We were ranked 2nd for both languages in this task.</abstract>
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%0 Conference Proceedings
%T Quartet@LT-EDI 2024: A SVM-ResNet50 Approach For Multitask Meme Classification - Unraveling Misogynistic and Trolls in Online Memes
%A H, Shaun
%A Sivakumar, Samyuktaa
%A R, Rohan
%A Jayaguptha, Nikilesh
%A Thenmozhi, Durairaj
%Y Chakravarthi, Bharathi Raja
%Y B, Bharathi
%Y Buitelaar, Paul
%Y Durairaj, Thenmozhi
%Y Kovács, György
%Y García Cumbreras, Miguel Ángel
%S Proceedings of the Fourth Workshop on Language Technology for Equality, Diversity, Inclusion
%D 2024
%8 March
%I Association for Computational Linguistics
%C St. Julian’s, Malta
%F h-etal-2024-quartet-lt
%X Meme is a very popular term prevailing among almost all social media platforms in recent days. A meme can be a combination of text and image whose sole purpose is meant to be funny and entertain people. Memes can sometimes promote misogynistic content expressing hatred, contempt, or prejudice against women. The Shared Task LT–EDI 2024: Multitask Meme Classification: Unraveling Misogynistic and Trolls in Online Memes Task 1 was created with the purpose to classify social media memes as “misogynistic” and “Non - Misogynistic”. The task encompassed Tamil and Malayalam datasets. We separately classified the textual data using Multinomial Naive Bayes and pictorial data using ResNet50 model. The results of from both data were combined to yield an overall result. We were ranked 2nd for both languages in this task.
%U https://aclanthology.org/2024.ltedi-1.27
%P 221-226
Markdown (Informal)
[Quartet@LT-EDI 2024: A SVM-ResNet50 Approach For Multitask Meme Classification - Unraveling Misogynistic and Trolls in Online Memes](https://aclanthology.org/2024.ltedi-1.27) (H et al., LTEDI-WS 2024)
ACL