MOMENTA: A Multimodal Framework for Detecting Harmful Memes and Their Targets
Published in EMNLP’21 (Findings), 2021
Recommended citation: Shraman Pramanick, Shivam Sharma, Dimitar Dimitrov, Md. Shad Akhtar, Preslav Nakov, and Tanmoy Chakraborty. 2021. MOMENTA: A Multimodal Framework for Detecting Harmful Memes and Their Targets. In Findings of the Association for Computational Linguistics: EMNLP 2021, pages 4439–4455, Punta Cana, Dominican Republic. Association for Computational Linguistics. https://aclanthology.org/2021.findings-emnlp.379/
Internet memes are powerful for communication, but harmful ones are rising, posing detection challenges. The study introduces MOMENTA, a neural network to detect harmful memes and identify their targets in a multimodal context. MOMENTA outperforms rivals, providing interpretability and generalizability.
Recommended citation: Shraman Pramanick, Shivam Sharma, Dimitar Dimitrov, Md. Shad Akhtar, Preslav Nakov, and Tanmoy Chakraborty. 2021. MOMENTA: A Multimodal Framework for Detecting Harmful Memes and Their Targets. In Findings of the Association for Computational Linguistics: EMNLP 2021, pages 4439–4455, Punta Cana, Dominican Republic. Association for Computational Linguistics.