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 | 3433-3443 |
| Number of pages | 11 |
| 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
Many argumentative texts, and news editorials in particular, follow a specific strategy to persuade their readers of some opinion or attitude. This includes decisions such as when to tell an anecdote or where to support an assumption with statistics, which is reflected by the composition of different types of argumentative discourse units in a text. While several argument mining corpora have recently been published, they do not allow the study of argumentation strategies due to incomplete or coarse-grained unit annotations. This paper presents a novel corpus with 300 editorials from three diverse news portals that provides the basis for mining argumentation strategies. Each unit in all editorials has been assigned one of six types by three annotators with a high Fleiss' K agreement of 0.56. We investigate various challenges of the annotation process and we conduct a first corpus analysis. Our results reveal different strategies across the news portals, exemplifying the benefit of studying editorials-a so far underresourced text genre in argument mining.
ASJC Scopus subject areas
- Computer Science(all)
- Computational Theory and Mathematics
- Arts and Humanities(all)
- Language and Linguistics
- Social Sciences(all)
- Linguistics and Language
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Proceedings of COLING 2016, the 26th International Conference on Computational Linguistics: Technical Papers. ed. / Yuji Matsumoto; Rashmi Prasad. 2016. p. 3433-3443.
Research output: Chapter in book/report/conference proceeding › Conference contribution › Research › peer review
}
TY - GEN
T1 - A News Editorial Corpus for Mining Argumentation Strategies
AU - Al-Khatib, Khalid
AU - Wachsmuth, Henning
AU - Kiesel, Johannes
AU - Hagen, Matthias
AU - Stein, Benno
PY - 2016/12
Y1 - 2016/12
N2 - Many argumentative texts, and news editorials in particular, follow a specific strategy to persuade their readers of some opinion or attitude. This includes decisions such as when to tell an anecdote or where to support an assumption with statistics, which is reflected by the composition of different types of argumentative discourse units in a text. While several argument mining corpora have recently been published, they do not allow the study of argumentation strategies due to incomplete or coarse-grained unit annotations. This paper presents a novel corpus with 300 editorials from three diverse news portals that provides the basis for mining argumentation strategies. Each unit in all editorials has been assigned one of six types by three annotators with a high Fleiss' K agreement of 0.56. We investigate various challenges of the annotation process and we conduct a first corpus analysis. Our results reveal different strategies across the news portals, exemplifying the benefit of studying editorials-a so far underresourced text genre in argument mining.
AB - Many argumentative texts, and news editorials in particular, follow a specific strategy to persuade their readers of some opinion or attitude. This includes decisions such as when to tell an anecdote or where to support an assumption with statistics, which is reflected by the composition of different types of argumentative discourse units in a text. While several argument mining corpora have recently been published, they do not allow the study of argumentation strategies due to incomplete or coarse-grained unit annotations. This paper presents a novel corpus with 300 editorials from three diverse news portals that provides the basis for mining argumentation strategies. Each unit in all editorials has been assigned one of six types by three annotators with a high Fleiss' K agreement of 0.56. We investigate various challenges of the annotation process and we conduct a first corpus analysis. Our results reveal different strategies across the news portals, exemplifying the benefit of studying editorials-a so far underresourced text genre in argument mining.
UR - http://www.scopus.com/inward/record.url?scp=85021686986&partnerID=8YFLogxK
M3 - Conference contribution
AN - SCOPUS:85021686986
SN - 9784879747020
SP - 3433
EP - 3443
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 -