Appropriate Incongruity Driven Human-AI Collaborative Tool to Assist Novices in Humorous Content Generation
Open accessAbstract
Creating humorous content has been shown to improve an individual’s emotional well-being by decreasing stress, overcoming anxiety, and enhancing interpersonal relationships. However, it is common knowledge that a good sense of humor is not common. In this paper, we propose a natural language processing (NLP) driven collaborative tool based on appropriate incongruity theory to assist novices in writing humorous content. We use cartoon-caption writing as the use case since it is a popular method where people engage in creating humorous content. The paper describes the design of our co-authoring tool and findings from a two-part user study where (1) 20 participants used our tool to co-author cartoon captions and (2) 66 participants evaluated those captions. Our findings show that the tool helped participants to identify incongruous visual elements in the cartoon, support ideation, and expand the narrative. This resulted in co-authored captions more frequently rated funnier than those written without the tool. This approach can be appropriated to other humor generation applications including creative writing, creating memes, sketch comedy, and advertising.
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- Authors
- Kariyawasam, H., Niwarthana, A., Palmer, A., Kay, J., & Withana, A.
- Affiliations
- The University of Sydney (AU)
- Venue
- Proceedings of the 29th International Conference on Intelligent User Interfaces
- Publisher
- ACM
- Published
- 2024-03-18
- Pages
- 650-659
- OpenAlex
- W4393970590
- Cited by
- 9
- References
- 35
- Citations by year
- 2026: 3 · 2025: 5 · 2024: 1
- FWCI
- 6.04
- Type
- conference paper
- Language
- en
- Open access
- bronze
- doi.org
- Locations
- ACM International Conference on Intelligent User Interfaces (IUI) (publishedVersion)
- Funders
- Australian Research Council (DE200100479)
- Topics
- Social Sciences › Psychology › Social Psychology › Humor Studies and Applications
- Physical Sciences › Computer Science › Human-Computer Interaction › Innovative Human-Technology Interaction
- Physical Sciences › Computer Science › Artificial Intelligence › Natural Language Processing Techniques
- Keywords
- humor generation, human-AI collaboration, novice writers, creative writing
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