Anshid Kizhakkeparambil


2024

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Overview of Shared Task on Multitask Meme Classification - Unraveling Misogynistic and Trolls in Online Memes
Bharathi Raja Chakravarthi | Saranya Rajiakodi | Rahul Ponnusamy | Kathiravan Pannerselvam | Anand Kumar Madasamy | Ramachandran Rajalakshmi | Hariharan LekshmiAmmal | Anshid Kizhakkeparambil | Susminu S Kumar | Bhuvaneswari Sivagnanam | Charmathi Rajkumar
Proceedings of the Fourth Workshop on Language Technology for Equality, Diversity, Inclusion

This paper offers a detailed overview of the first shared task on “Multitask Meme Classification - Unraveling Misogynistic and Trolls in Online Memes,” organized as part of the LT-EDI@EACL 2024 conference. The task was set to classify misogynistic content and troll memes within online platforms, focusing specifically on memes in Tamil and Malayalam languages. A total of 52 teams registered for the competition, with four submitting systems for the Tamil meme classification task and three for the Malayalam task. The outcomes of this shared task are significant, providing insights into the current state of misogynistic content in digital memes and highlighting the effectiveness of various computational approaches in identifying such detrimental content. The top-performing model got a macro F1 score of 0.73 in Tamil and 0.87 in Malayalam.