Exploiting Syntactic Structures for Humor Recognition

Lizhen Liu, Donghai Zhang, Wei Song


Abstract
Humor recognition is an interesting and challenging task in natural language processing. This paper proposes to exploit syntactic structure features to enhance humor recognition. Our method achieves significant improvements compared with humor theory driven baselines. We found that some syntactic structure features consistently correlate with humor, which indicate interesting linguistic phenomena. Both the experimental results and the analysis demonstrate that humor can be viewed as a kind of style and content independent syntactic structures can help identify humor and have good interpretability.
Anthology ID:
C18-1159
Volume:
Proceedings of the 27th International Conference on Computational Linguistics
Month:
August
Year:
2018
Address:
Santa Fe, New Mexico, USA
Venue:
COLING
SIG:
Publisher:
Association for Computational Linguistics
Note:
Pages:
1875–1883
Language:
URL:
https://aclanthology.org/C18-1159
DOI:
Bibkey:
Cite (ACL):
Lizhen Liu, Donghai Zhang, and Wei Song. 2018. Exploiting Syntactic Structures for Humor Recognition. In Proceedings of the 27th International Conference on Computational Linguistics, pages 1875–1883, Santa Fe, New Mexico, USA. Association for Computational Linguistics.
Cite (Informal):
Exploiting Syntactic Structures for Humor Recognition (Liu et al., COLING 2018)
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PDF:
https://preview.aclanthology.org/paclic-22-ingestion/C18-1159.pdf