Determining Relative Argument Specificity and Stance for Complex Argumentative Structures
Not on the map. Why?
Abstract (arXiv)
Systems for automatic argument generation and debate require the ability to (1) determine the stance of any claims employed in the argument and (2) assess the specificity of each claim relative to the argument context. Existing work on understanding claim specificity and stance, however, has been limited to the study of argumentative structures that are relatively shallow, most often consisting of a single claim that directly supports or opposes the argument thesis. In this paper, we tackle these tasks in the context of complex arguments on a diverse set of topics. In particular, our dataset consists of manually curated argument trees for 741 controversial topics covering 95,312 unique claims; lines of argument are generally of depth 2 to 6. We find that as the distance between a pair of claims increases along the argument path, determining the relative specificity of a pair of claims becomes easier and determining their relative stance becomes harder.
Key facts. Cited by 7 papers in the map (data through 7 Oct 2026). First posted on arXiv 26 Jun 2019.
Builds on
No reference list yet.
Built on by
Citing papers per year: 2021: 4; 2022: 0; 2023: 0; 2024: 1; 2025: 1; 2026: 1.
7 papers.
- 2021Human-in-the-Loop for Data Collection: a Multi-Target Counter Narrative Dataset to Fight Online Hate Speechcited by 81
- 2021Classifying Argumentative Relations Using Logical Mechanisms and Argumentation Schemescited by 17
- 2021Scientia Potentia Est -- On the Role of Knowledge in Computational Argumentationcited by 17
- 2021Generating Informative Conclusions for Argumentative Textscited by 14
- 2024Putting Context in Context: the Impact of Discussion Structure on Text Classificationcited by 3
- 2025Do Language Models Think Consistently? A Study of Value Preferences Across Varying Response Lengthscited by 2
- 2026ArgBench: Benchmarking LLMs on Computational Argumentation Taskscited by 1
- 2026ArgBench: Benchmarking LLMs on Computational Argumentation Tasks19 Apr 2026
- 2025Do Language Models Think Consistently? A Study of Value Preferences Across Varying Response Lengths3 Jun 2025
- 2024Putting Context in Context: the Impact of Discussion Structure on Text Classification5 Feb 2024
- 2021Human-in-the-Loop for Data Collection: a Multi-Target Counter Narrative Dataset to Fight Online Hate Speech19 Jul 2021
- 2021Scientia Potentia Est -- On the Role of Knowledge in Computational Argumentation1 Jul 2021
- 2021Generating Informative Conclusions for Argumentative Texts2 Jun 2021
- 2021Classifying Argumentative Relations Using Logical Mechanisms and Argumentation Schemes17 May 2021