The Naughtyformer: A Transformer Understands and Moderates Adult Humor (Student Abstract)
Keywords:Data Mining, Natural Language Processing, Computational Social Science, Transformers, Humor Detection, Offensiveness Detection
AbstractJokes are intentionally written to be funny, but not all jokes are created the same. While recent work has shown impressive results on humor detection in text, we instead investigate the more nuanced task of detecting humor subtypes, especially of the more adult variety. To that end, we introduce a novel jokes dataset filtered from Reddit and solve the subtype classification task using a finetuned Transformer dubbed the Naughtyformer. Moreover, we show that our model is significantly better at detecting offensiveness in jokes compared to state-of-the-art methods.
How to Cite
Tang, L., Cai, A., & Wang, J. (2023). The Naughtyformer: A Transformer Understands and Moderates Adult Humor (Student Abstract). Proceedings of the AAAI Conference on Artificial Intelligence, 37(13), 16348-16349. https://doi.org/10.1609/aaai.v37i13.27034
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