Linguistic Features of Sarcasm and Metaphor Production Quality

Stephen Skalicky, Scott Crossley


Abstract
Using linguistic features to detect figurative language has provided a deeper in-sight into figurative language. The purpose of this study is to assess whether linguistic features can help explain differences in quality of figurative language. In this study a large corpus of metaphors and sarcastic responses are collected from human subjects and rated for figurative language quality based on theoretical components of metaphor, sarcasm, and creativity. Using natural language processing tools, specific linguistic features related to lexical sophistication and semantic cohesion were used to predict the human ratings of figurative language quality. Results demonstrate linguistic features were able to predict small amounts of variance in metaphor and sarcasm production quality.
Anthology ID:
W18-0902
Volume:
Proceedings of the Workshop on Figurative Language Processing
Month:
June
Year:
2018
Address:
New Orleans, Louisiana
Editors:
Beata Beigman Klebanov, Ekaterina Shutova, Patricia Lichtenstein, Smaranda Muresan, Chee Wee
Venue:
Fig-Lang
SIG:
Publisher:
Association for Computational Linguistics
Note:
Pages:
7–16
Language:
URL:
https://aclanthology.org/W18-0902
DOI:
10.18653/v1/W18-0902
Bibkey:
Cite (ACL):
Stephen Skalicky and Scott Crossley. 2018. Linguistic Features of Sarcasm and Metaphor Production Quality. In Proceedings of the Workshop on Figurative Language Processing, pages 7–16, New Orleans, Louisiana. Association for Computational Linguistics.
Cite (Informal):
Linguistic Features of Sarcasm and Metaphor Production Quality (Skalicky & Crossley, Fig-Lang 2018)
Copy Citation:
PDF:
https://aclanthology.org/W18-0902.pdf