TeamX@DravidianLangTech-ACL2022: A Comparative Analysis for Troll-Based Meme Classification

• URL: http://arxiv.org/abs/2205.04404v1
• Date: Mon, 9 May 2022 16:19:28 GMT
• Title: TeamX@DravidianLangTech-ACL2022: A Comparative Analysis for Troll-Based Meme Classification
• Authors: Rabindra Nath Nandi, Firoj Alam, Preslav Nakov
• Abstract summary: harmful content online raised concerns among social media platforms, government agencies, policymakers, and society as a whole. Among different harmful content textittrolling-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. This study provides a comparative analysis of troll-based memes classification using the textual, visual, and multimodal content.
• Score: 21.32190107220764
• License: http://creativecommons.org/licenses/by-nc-nd/4.0/
• Abstract: 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 \textit{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.

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