Style is NOT a single variable: Case Studies for Cross-Stylistic Language Understanding

Dongyeop Kang, Eduard Hovy


Abstract
Every natural text is written in some style. Style is formed by a complex combination of different stylistic factors, including formality markers, emotions, metaphors, etc. One cannot form a complete understanding of a text without considering these factors. The factors combine and co-vary in complex ways to form styles. Studying the nature of the covarying combinations sheds light on stylistic language in general, sometimes called cross-style language understanding. This paper provides the benchmark corpus (XSLUE) that combines existing datasets and collects a new one for sentence-level cross-style language understanding and evaluation. The benchmark contains text in 15 different styles under the proposed four theoretical groupings: figurative, personal, affective, and interpersonal groups. For valid evaluation, we collect an additional diagnostic set by annotating all 15 styles on the same text. Using XSLUE, we propose three interesting cross-style applications in classification, correlation, and generation. First, our proposed cross-style classifier trained with multiple styles together helps improve overall classification performance against individually-trained style classifiers. Second, our study shows that some styles are highly dependent on each other in human-written text. Finally, we find that combinations of some contradictive styles likely generate stylistically less appropriate text. We believe our benchmark and case studies help explore interesting future directions for cross-style research. The preprocessed datasets and code are publicly available.
Anthology ID:
2021.acl-long.185
Volume:
Proceedings of the 59th Annual Meeting of the Association for Computational Linguistics and the 11th International Joint Conference on Natural Language Processing (Volume 1: Long Papers)
Month:
August
Year:
2021
Address:
Online
Editors:
Chengqing Zong, Fei Xia, Wenjie Li, Roberto Navigli
Venues:
ACL | IJCNLP
SIG:
Publisher:
Association for Computational Linguistics
Note:
Pages:
2376–2387
Language:
URL:
https://aclanthology.org/2021.acl-long.185
DOI:
10.18653/v1/2021.acl-long.185
Bibkey:
Cite (ACL):
Dongyeop Kang and Eduard Hovy. 2021. Style is NOT a single variable: Case Studies for Cross-Stylistic Language Understanding. In Proceedings of the 59th Annual Meeting of the Association for Computational Linguistics and the 11th International Joint Conference on Natural Language Processing (Volume 1: Long Papers), pages 2376–2387, Online. Association for Computational Linguistics.
Cite (Informal):
Style is NOT a single variable: Case Studies for Cross-Stylistic Language Understanding (Kang & Hovy, ACL-IJCNLP 2021)
Copy Citation:
PDF:
https://aclanthology.org/2021.acl-long.185.pdf
Optional supplementary material:
 2021.acl-long.185.OptionalSupplementaryMaterial.pdf
Video:
 https://aclanthology.org/2021.acl-long.185.mp4
Code
 dykang/xslue
Data
DailyDialogEmoBankGYAFCPASTELSARC