Stimulating Creativity with FunLines: A Case Study of Humor Generation in Headlines

Nabil Hossain, John Krumm, Tanvir Sajed, Henry Kautz


Abstract
Building datasets of creative text, such as humor, is quite challenging. We introduce FunLines, a competitive game where players edit news headlines to make them funny, and where they rate the funniness of headlines edited by others. FunLines makes the humor generation process fun, interactive, collaborative, rewarding and educational, keeping players engaged and providing humor data at a very low cost compared to traditional crowdsourcing approaches. FunLines offers useful performance feedback, assisting players in getting better over time at generating and assessing humor, as our analysis shows. This helps to further increase the quality of the generated dataset. We show the effectiveness of this data by training humor classification models that outperform a previous benchmark, and we release this dataset to the public.
Anthology ID:
2020.acl-demos.28
Volume:
Proceedings of the 58th Annual Meeting of the Association for Computational Linguistics: System Demonstrations
Month:
July
Year:
2020
Address:
Online
Venue:
ACL
SIG:
Publisher:
Association for Computational Linguistics
Note:
Pages:
256–262
Language:
URL:
https://www.aclweb.org/anthology/2020.acl-demos.28
DOI:
10.18653/v1/2020.acl-demos.28
Bib Export formats:
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PDF:
http://aclanthology.lst.uni-saarland.de/2020.acl-demos.28.pdf
Video:
 http://slideslive.com/38928614