Abstract
We define an argumentation strategy as the set of rhetorical and stylistic means that authors employ to produce an effective, and often persuasive, text. First computational accounts of such strategies have been relatively coarse-grained, while in our work we aim to move to a more detailed analysis. We extend the annotations of the Argument Annotated Essays corpus (Stab and Gurevych, 2017) with specific types of claims and premises, propose a model for their automatic identification and show first results, and then we discuss usage patterns that emerge with respect to the essay structure, the “flows” of argument component types, the claim-premise constellations, the role of the essay prompt type, and that of the individual author.- Anthology ID:
- 2023.argmining-1.8
- 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:
- 76–88
- Language:
- URL:
- https://aclanthology.org/2023.argmining-1.8
- DOI:
- 10.18653/v1/2023.argmining-1.8
- Cite (ACL):
- Robin Schaefer, René Knaebel, and Manfred Stede. 2023. Towards Fine-Grained Argumentation Strategy Analysis in Persuasive Essays. In Proceedings of the 10th Workshop on Argument Mining, pages 76–88, Singapore. Association for Computational Linguistics.
- Cite (Informal):
- Towards Fine-Grained Argumentation Strategy Analysis in Persuasive Essays (Schaefer et al., ArgMining-WS 2023)
- PDF:
- https://preview.aclanthology.org/ingest-acl-2023-videos/2023.argmining-1.8.pdf