Different knowledge, same joke: Response-based computational detection of humor

Abstract

The paper explores the very basis of linguistic theories of humor with a view of applying them to computational humor. Computation requires tighter definitions. The paper analyzes joke-carrying texts based on the existing script-based methods. It compares jokes that have the same setup but different punchlines by examining the background knowledge that should be available to detect humor. It then moves into jokes where the same joke text elicits different responses from the reader, and conjectures that the responses are based on the readers’ world knowledge and preferences. Such responses make it possible not only to analyze humor, but also to understand more about the people that produce the responses.