Abstract
Although humor enriches human lives, some jokes fail to amuse people because of a lack of morality. In this paper, we propose a mechanism capable of selecting humor based on moral criteria. To this end, we first construct a model based on an N-gram corpus and generate joke candidates using various template patterns. We then employ a moral judgement classifier based on a recurrent neural network and utilize the trained model for humor selection. The experimental results obtained from best–worst scaling demonstrate that this scheme is able to generate jokes with moral category labels. We confirmed that jokes about the classifier categorized as Loyalty and Authority, which are regarded as good in our study, are funnier than jokes about Fairness, Purity, Harm, Cheating, and Degradation. Although we did not confirm that there was a difference in the funny level between good and bad moral jokes, the results demonstrate that moral categories of humor can affect the funny level.
Published Version
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Disclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.