Abstract
In this system paper for SemEval-2024 Task4 subtask 2b, I present my approach to identifying propagandistic memes in multiple languages. I firstly establish a baseline for Englishand then implement the model into other languages (Bulgarian, North Macedonian and Arabic) by using machine translation. Data fromother subtasks (subtask 1, subtask 2a) are alsoused in addition to data for this subtask, andadditional data from Kaggle are concatenatedto these in order to enhance the model. Theresults show a high reliability of my Englishbaseline and a room for improvement of itsimplementation.- Anthology ID:
- 2024.semeval-1.57
- Volume:
- Proceedings of the 18th International Workshop on Semantic Evaluation (SemEval-2024)
- Month:
- June
- Year:
- 2024
- Address:
- Mexico City, Mexico
- Editors:
- Atul Kr. Ojha, A. Seza Doğruöz, Harish Tayyar Madabushi, Giovanni Da San Martino, Sara Rosenthal, Aiala Rosá
- Venue:
- SemEval
- SIG:
- SIGLEX
- Publisher:
- Association for Computational Linguistics
- Note:
- Pages:
- 370–373
- Language:
- URL:
- https://aclanthology.org/2024.semeval-1.57
- DOI:
- 10.18653/v1/2024.semeval-1.57
- Cite (ACL):
- Hidetsune Takahashi. 2024. Hidetsune at SemEval-2024 Task 4: An Application of Machine Learning to Multilingual Propagandistic Memes Identification Using Machine Translation. In Proceedings of the 18th International Workshop on Semantic Evaluation (SemEval-2024), pages 370–373, Mexico City, Mexico. Association for Computational Linguistics.
- Cite (Informal):
- Hidetsune at SemEval-2024 Task 4: An Application of Machine Learning to Multilingual Propagandistic Memes Identification Using Machine Translation (Takahashi, SemEval 2024)
- PDF:
- https://preview.aclanthology.org/nschneid-patch-4/2024.semeval-1.57.pdf