Details
| Original language | English |
|---|---|
| Title of host publication | Proceedings of COLING 2016, the 26th International Conference on Computational Linguistics |
| Subtitle of host publication | Technical Papers |
| Editors | Yuji Matsumoto, Rashmi Prasad |
| Pages | 1680-1691 |
| Number of pages | 12 |
| Publication status | Published - Dec 2016 |
| Externally published | Yes |
| Event | 26th International Conference on Computational Linguistics, COLING 2016 - Osaka, Japan Duration: 11 Dec 2016 → 17 Dec 2016 |
Abstract
Argument mining aims to determine the argumentative structure of texts. Although it is said to be crucial for future applications such as writing support systems, the benefit of its output has rarely been evaluated. This paper puts the analysis of the output into the focus. In particular, we investigate to what extent the mined structure can be leveraged to assess the argumentation quality of persuasive essays. We find insightful statistical patterns in the structure of essays. From these, we derive novel features that we evaluate in four argumentation-related essay scoring tasks. Our results reveal the benefit of argument mining for assessing argumentation quality. Among others, we improve the state of the art in scoring an essay's organization and its argument strength.
ASJC Scopus subject areas
- Computer Science(all)
- Computational Theory and Mathematics
- Arts and Humanities(all)
- Language and Linguistics
- Social Sciences(all)
- Linguistics and Language
Cite this
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Proceedings of COLING 2016, the 26th International Conference on Computational Linguistics: Technical Papers. ed. / Yuji Matsumoto; Rashmi Prasad. 2016. p. 1680-1691.
Research output: Chapter in book/report/conference proceeding › Conference contribution › Research › peer review
}
TY - GEN
T1 - Using Argument Mining to Assess the Argumentation Quality of Essays
AU - Wachsmuth, Henning
AU - Al-Khatib, Khalid
AU - Stein, Benno
PY - 2016/12
Y1 - 2016/12
N2 - Argument mining aims to determine the argumentative structure of texts. Although it is said to be crucial for future applications such as writing support systems, the benefit of its output has rarely been evaluated. This paper puts the analysis of the output into the focus. In particular, we investigate to what extent the mined structure can be leveraged to assess the argumentation quality of persuasive essays. We find insightful statistical patterns in the structure of essays. From these, we derive novel features that we evaluate in four argumentation-related essay scoring tasks. Our results reveal the benefit of argument mining for assessing argumentation quality. Among others, we improve the state of the art in scoring an essay's organization and its argument strength.
AB - Argument mining aims to determine the argumentative structure of texts. Although it is said to be crucial for future applications such as writing support systems, the benefit of its output has rarely been evaluated. This paper puts the analysis of the output into the focus. In particular, we investigate to what extent the mined structure can be leveraged to assess the argumentation quality of persuasive essays. We find insightful statistical patterns in the structure of essays. From these, we derive novel features that we evaluate in four argumentation-related essay scoring tasks. Our results reveal the benefit of argument mining for assessing argumentation quality. Among others, we improve the state of the art in scoring an essay's organization and its argument strength.
UR - http://www.scopus.com/inward/record.url?scp=85021679474&partnerID=8YFLogxK
M3 - Conference contribution
AN - SCOPUS:85021679474
SN - 9784879747020
SP - 1680
EP - 1691
BT - Proceedings of COLING 2016, the 26th International Conference on Computational Linguistics
A2 - Matsumoto, Yuji
A2 - Prasad, Rashmi
T2 - 26th International Conference on Computational Linguistics, COLING 2016
Y2 - 11 December 2016 through 17 December 2016
ER -