Details
| Original language | English |
|---|---|
| Title of host publication | Proceedings of the 61st Annual Meeting of the Association for Computational Linguistics |
| Pages | 4344-4363 |
| Number of pages | 20 |
| ISBN (electronic) | 9781959429722 |
| Publication status | Published - Jul 2023 |
| Event | 61st Annual Meeting of the Association for Computational Linguistics, ACL 2023 - Toronto, Canada Duration: 9 Jul 2023 → 14 Jul 2023 |
Publication series
| Name | Proceedings of the Annual Meeting of the Association for Computational Linguistics |
|---|---|
| Volume | 1 |
| ISSN (Print) | 0736-587X |
Abstract
ASJC Scopus subject areas
- Computer Science(all)
- Computer Science Applications
- Social Sciences(all)
- Linguistics and Language
- Arts and Humanities(all)
- Language and Linguistics
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Proceedings of the 61st Annual Meeting of the Association for Computational Linguistics. 2023. p. 4344-4363 (Proceedings of the Annual Meeting of the Association for Computational Linguistics; Vol. 1).
Research output: Chapter in book/report/conference proceeding › Conference contribution › Research › peer review
}
TY - GEN
T1 - Modeling Appropriate Language in Argumentation
AU - Ziegenbein, Timon
AU - Syed, Shahbaz
AU - Lange, Felix
AU - Potthast, Martin
AU - Wachsmuth, Henning
N1 - Funding Information: This project has been partially funded by the German Research Foundation (DFG) within the project OASiS, project number 455913891, as part of the Priority Program “Robust Argumentation Machines (RATIO)” (SPP-1999). We would like to thank the participants of our study and the anonymous reviewers for the feedback and their time.
PY - 2023/7
Y1 - 2023/7
N2 - Online discussion moderators must make ad-hoc decisions about whether the contributions of discussion participants are appropriate or should be removed to maintain civility. Existing research on offensive language and the resulting tools cover only one aspect among many involved in such decisions. The question of what is considered appropriate in a controversial discussion has not yet been systematically addressed. In this paper, we operationalize appropriate language in argumentation for the first time. In particular, we model appropriateness through the absence of flaws, grounded in research on argument quality assessment, especially in aspects from rhetoric. From these, we derive a new taxonomy of 14 dimensions that determine inappropriate language in online discussions. Building on three argument quality corpora, we then create a corpus of 2191 arguments annotated for the 14 dimensions. Empirical analyses support that the taxonomy covers the concept of appropriateness comprehensively, showing several plausible correlations with argument quality dimensions. Moreover, results of baseline approaches to assessing appropriateness suggest that all dimensions can be modeled computationally on the corpus.
AB - Online discussion moderators must make ad-hoc decisions about whether the contributions of discussion participants are appropriate or should be removed to maintain civility. Existing research on offensive language and the resulting tools cover only one aspect among many involved in such decisions. The question of what is considered appropriate in a controversial discussion has not yet been systematically addressed. In this paper, we operationalize appropriate language in argumentation for the first time. In particular, we model appropriateness through the absence of flaws, grounded in research on argument quality assessment, especially in aspects from rhetoric. From these, we derive a new taxonomy of 14 dimensions that determine inappropriate language in online discussions. Building on three argument quality corpora, we then create a corpus of 2191 arguments annotated for the 14 dimensions. Empirical analyses support that the taxonomy covers the concept of appropriateness comprehensively, showing several plausible correlations with argument quality dimensions. Moreover, results of baseline approaches to assessing appropriateness suggest that all dimensions can be modeled computationally on the corpus.
UR - http://www.scopus.com/inward/record.url?scp=85174374271&partnerID=8YFLogxK
U2 - 10.18653/v1/2023.acl-long.238
DO - 10.18653/v1/2023.acl-long.238
M3 - Conference contribution
T3 - Proceedings of the Annual Meeting of the Association for Computational Linguistics
SP - 4344
EP - 4363
BT - Proceedings of the 61st Annual Meeting of the Association for Computational Linguistics
T2 - 61st Annual Meeting of the Association for Computational Linguistics, ACL 2023
Y2 - 9 July 2023 through 14 July 2023
ER -