Abstract
This paper presents an overview of the ImageArg shared task, the first multimodal Argument Mining shared task co-located with the 10th Workshop on Argument Mining at EMNLP 2023. The shared task comprises two classification subtasks - (1) Subtask-A: Argument Stance Classification; (2) Subtask-B: Image Persuasiveness Classification. The former determines the stance of a tweet containing an image and a piece of text toward a controversial topic (e.g., gun control and abortion). The latter determines whether the image makes the tweet text more persuasive. The shared task received 31 submissions for Subtask-A and 21 submissions for Subtask-B from 9 different teams across 6 countries. The top submission in Subtask-A achieved an F1-score of 0.8647 while the best submission in Subtask-B achieved an F1-score of 0.5561.- Anthology ID:
- 2023.argmining-1.12
- 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:
- 120–132
- Language:
- URL:
- https://aclanthology.org/2023.argmining-1.12
- DOI:
- 10.18653/v1/2023.argmining-1.12
- Cite (ACL):
- Zhexiong Liu, Mohamed Elaraby, Yang Zhong, and Diane Litman. 2023. Overview of ImageArg-2023: The First Shared Task in Multimodal Argument Mining. In Proceedings of the 10th Workshop on Argument Mining, pages 120–132, Singapore. Association for Computational Linguistics.
- Cite (Informal):
- Overview of ImageArg-2023: The First Shared Task in Multimodal Argument Mining (Liu et al., ArgMining-WS 2023)
- PDF:
- https://preview.aclanthology.org/ingest-acl-2023-videos/2023.argmining-1.12.pdf