Humor meets morality: Joke generation based on moral judgement. Issue 3 (May 2021)

• Record Type: Journal Article
• Authors: Yamane, Hiroaki; Mori, Yusuke; Harada, Tatsuya
• Is Part Of: Information processing & management. Volume 58:Issue 3(2021)
• Publication Date: 2021-05
• Subjects: Computational humor -- Morality -- Recurrent neural networks -- Joke generation; Information storage and retrieval systems -- Periodicals; Information science -- Periodicals; Systèmes d'information -- Périodiques; Sciences de l'information -- Périodiques; Information science; Information storage and retrieval systems; Periodicals; 658.4038
• DOI: 10.1016/j.ipm.2021.102520
• Languages: English
• ISSNs: 0306-4573

Abstract

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. Highlights: A mechanism capable of selecting humor based on moral criteria was proposed. A survey was conducted to link humor and morality by explaining the theory of mind. A scheme to generate morally positive/negative jokes using both the template extended model constructed from N -gram corpus and the moral classifier.