Verifying Claims About Metaphors with Large-Scale Automatic Metaphor Identification

Kotaro Aono, Ryohei Sasano, Koichi Takeda


Abstract
There are several linguistic claims about situations where words are more likely to be used as metaphors.However, few studies have sought to verify such claims with large corpora.This study entails a large-scale, corpus-based analysis of certain existing claims about verb metaphors, by applying metaphor detection to sentences extracted from Common Crawl and using the statistics obtained from the results.The verification results indicate that the direct objects of verbs used as metaphors tend to have lower degrees of concreteness, imageability, and familiarity, and that metaphors are more likely to be used in emotional and subjective sentences.
Anthology ID:
2024.naacl-short.62
Volume:
Proceedings of the 2024 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies (Volume 2: Short Papers)
Month:
June
Year:
2024
Address:
Mexico City, Mexico
Editors:
Kevin Duh, Helena Gomez, Steven Bethard
Venue:
NAACL
SIG:
Publisher:
Association for Computational Linguistics
Note:
Pages:
711–719
Language:
URL:
https://aclanthology.org/2024.naacl-short.62
DOI:
10.18653/v1/2024.naacl-short.62
Bibkey:
Cite (ACL):
Kotaro Aono, Ryohei Sasano, and Koichi Takeda. 2024. Verifying Claims About Metaphors with Large-Scale Automatic Metaphor Identification. In Proceedings of the 2024 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies (Volume 2: Short Papers), pages 711–719, Mexico City, Mexico. Association for Computational Linguistics.
Cite (Informal):
Verifying Claims About Metaphors with Large-Scale Automatic Metaphor Identification (Aono et al., NAACL 2024)
Copy Citation:
PDF:
https://aclanthology.org/2024.naacl-short.62.pdf