Graduate Project Title
Visualizing Incongruity: Visual Data Mining Strategies for Modeling Humor in Text
Document Type
Graduate Project
Date of Degree Completion
Fall 2017
Degree Name
Master of Science (MS)
Department
Computational Science
Committee Chair
Boris Kovalerchuk
Second Committee Member
Razvan Andonie
Third Committee Member
Szilard Vajda
Abstract
The goal of this project is to investigate the use of visual data mining to model verbal humor. We explored various means of text visualization to identify key featrues of garden path jokes as compared with non jokes. With garden path jokes one interpretation is established in the setup but new information indicating some alternative interpretation triggers some resolution process leading to a new interpretation. For this project we visualize text in three novel ways, assisted by some web mining to build an informal ontology, that allow us to see the differences between garden path jokes and non jokes of similar form. We used the results of the visualizations to build a rule based model which was then compared with models from tradtitional data mining toi show the use of visual data mining. Additional experiments with other forms of incongruity including visualization of ’shilling’ or the introduction of false reviews into a product review set. The results are very similar to that of garden path jokes and start to show us there is a shape to incongruity. Overall this project shows as that the proposed methodologies and tools offer a new approach to testing and generating hypotheses related to theories of humor as well as other phenomena involving opposition, incongruities, and shifts in classification.
Recommended Citation
Smigaj, Andrew, "Visualizing Incongruity: Visual Data Mining Strategies for Modeling Humor in Text" (2017). All Graduate Projects. 163.
https://digitalcommons.cwu.edu/graduate_projects/163