Abstract
We describe the UTFPR system for SemEval-2020’s Task 7: Assessing Humor in Edited News Headlines. Ours is a minimalist unsupervised system that uses word co-occurrence frequencies from large corpora to capture unexpectedness as a mean to capture funniness. Our system placed 22nd on the shared task’s Task 2. We found that our approach requires more text than we used to perform reliably, and that unexpectedness alone is not sufficient to gauge funniness for humorous content that targets a diverse target audience.- Anthology ID:
- 2020.semeval-1.140
- Volume:
- Proceedings of the Fourteenth Workshop on Semantic Evaluation
- Month:
- December
- Year:
- 2020
- Address:
- Barcelona (online)
- Editors:
- Aurelie Herbelot, Xiaodan Zhu, Alexis Palmer, Nathan Schneider, Jonathan May, Ekaterina Shutova
- Venue:
- SemEval
- SIG:
- SIGLEX
- Publisher:
- International Committee for Computational Linguistics
- Note:
- Pages:
- 1066–1070
- Language:
- URL:
- https://aclanthology.org/2020.semeval-1.140
- DOI:
- 10.18653/v1/2020.semeval-1.140
- Cite (ACL):
- Gustavo Henrique Paetzold. 2020. UTFPR at SemEval-2020 Task 7: Using Co-occurrence Frequencies to Capture Unexpectedness. In Proceedings of the Fourteenth Workshop on Semantic Evaluation, pages 1066–1070, Barcelona (online). International Committee for Computational Linguistics.
- Cite (Informal):
- UTFPR at SemEval-2020 Task 7: Using Co-occurrence Frequencies to Capture Unexpectedness (Paetzold, SemEval 2020)
- PDF:
- https://preview.aclanthology.org/fix-volume-bibkeys/2020.semeval-1.140.pdf