IUST at ImageArg: The First Shared Task in Multimodal Argument Mining
Melika Nobakhtian, Ghazal Zamaninejad, Erfan Moosavi Monazzah, Sauleh Eetemadi
Abstract
ImageArg is a shared task at the 10th ArgMining Workshop at EMNLP 2023. It leverages the ImageArg dataset to advance multimodal persuasiveness techniques. This challenge comprises two distinct subtasks: 1) Argumentative Stance (AS) Classification: Assessing whether a given tweet adopts an argumentative stance. 2) Image Persuasiveness (IP) Classification: Determining if the tweet image enhances the persuasive quality of the tweet. We conducted various experiments on both subtasks and ranked sixth out of the nine participating teams.- Anthology ID:
- 2023.argmining-1.13
- Volume:
- Proceedings of the 10th Workshop on Argument Mining
- Month:
- December
- Year:
- 2023
- Address:
- Singapore
- Editors:
- Milad Alshomary, Chung-Chi Chen, Smaranda Muresan, Joonsuk Park, Julia Romberg
- Venues:
- ArgMining | WS
- SIG:
- Publisher:
- Association for Computational Linguistics
- Note:
- Pages:
- 133–138
- Language:
- URL:
- https://aclanthology.org/2023.argmining-1.13
- DOI:
- 10.18653/v1/2023.argmining-1.13
- Cite (ACL):
- Melika Nobakhtian, Ghazal Zamaninejad, Erfan Moosavi Monazzah, and Sauleh Eetemadi. 2023. IUST at ImageArg: The First Shared Task in Multimodal Argument Mining. In Proceedings of the 10th Workshop on Argument Mining, pages 133–138, Singapore. Association for Computational Linguistics.
- Cite (Informal):
- IUST at ImageArg: The First Shared Task in Multimodal Argument Mining (Nobakhtian et al., ArgMining-WS 2023)
- PDF:
- https://preview.aclanthology.org/naacl24-info/2023.argmining-1.13.pdf