Quartet@LT-EDI 2024: A SVM-ResNet50 Approach For Multitask Meme Classification - Unraveling Misogynistic and Trolls in Online Memes
Abstract
AbstractMeme 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.