The DOI matches its Crossref record; 83 of the 83 references it cites were found in a registry or an index.
Parsing Argumentation Structures in Persuasive Essays
Open accessAbstract
In this article, we present a novel approach for parsing argumentation structures. We identify argument components using sequence labeling at the token level and apply a new joint model for detecting argumentation structures. The proposed model globally optimizes argument component types and argumentative relations using Integer Linear Programming. We show that our model significantly outperforms challenging heuristic baselines on two different types of discourse. Moreover, we introduce a novel corpus of persuasive essays annotated with argumentation structures. We show that our annotation scheme and annotation guidelines successfully guide human annotators to substantial agreement.
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Cited by
Lawrence, J., & Reed, C. (2020) · Computational Linguistics · doi:10.1162/coli_a_00364 · Cited by 396
ArgueTutor: An Adaptive Dialog-Based Learning System for Argumentation Skills
Wambsganss, T., Kueng, T., Soellner, M., & Leimeister, J. M. (2021) · Proceedings of the 2021 CHI Conference on Human Factors in Computing Systems · doi:10.1145/3411764.3445781 · Cited by 138
Seeing Things from a Different Angle:Discovering Diverse Perspectives about Claims
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Argument Mining for Understanding Peer Reviews
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Enhancing evidence-based medicine with natural language argumentative analysis of clinical trials.
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Metadata
- Authors
- Stab, C., & Gurevych, I.
- Venue
- Computational Linguistics
- Publisher
- MIT Press
- Published
- 2017-09
- Volume
- 43
- Issue
- 3
- Pages
- 619-659
- ISSN
- 0891-2017 (ISSN-L)
- 1530-9312
- OpenAlex
- W2343649478
- Cited by
- 388
- References
- 83
- FWCI
- 24.27
- Type
- journal article
- Language
- en
- Open access
- diamond
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