TeamX@DravidianLangTech-ACL2022: A Comparative Analysis for Troll-Based Meme Classification
Rabindra Nath Nandi, Firoj Alam, Preslav Nakov · 2022
The spread of fake news, propaganda, misinformation, disinformation, and harmful content online raised concerns among social media platforms, government agencies, policymakers, and society as a whole.This is because such harmful or abusive content leads to several consequences to people such as physical, emotional, relational, and financial.Among different harmful content trolling-based online content is one of them, where the idea is to post a message that is provocative, offensive, or menacing with an intent to mislead the audience.The content can be textual, visual, a combination of both, or a meme.In this study, we provide a comparative analysis of troll-based memes classification using the textual, visual, and multimodal content.We report several interesting findings in terms of code-mixed text, multimodal setting, and combining an additional dataset, which shows improvements over the majority baseline.