Designing a Multiplayer Competitive Text-Based Game for Elicitation of Tacit Knowledge About Humor from Crowds of People

Bachelor thesis (2021)

Authors

M.T. Schop Electrical Engineering, Mathematics and Computer Science

Contributors

A.M.A. Balayn Web Information Systems - EEMCS (supervisor 1)
Ujwal Gadiraju Web Information Systems - EEMCS (supervisor 2)
J. Yang Web Information Systems - EEMCS (supervisor 2)
B.H.M. Gerritsen Computer Science & Engineering-Teaching Team - EEMCS (coach)
Faculty
Electrical Engineering, Mathematics and Computer Science
Copyright: © 2021 Melvin Schop
Machine Learning Tacit Knowledge Game Design Humor
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Published Date

02-07-2021

Language

English

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Faculty

Electrical Engineering, Mathematics and Computer Science

Abstract

Tacit knowledge, unlike explicit knowledge, is not easily codifiable, yet important for machine learning models. This research explores a method to gather tacit knowledge about humor using a simple text-based party game, building on the existing idea of using games to gather tacit knowledge from crowds of people. Players propose prompts, which will then be answered by other players. They will then vote to determine which of the two answers to each prompt is the funniest. The engagement of the players with the game is measured and tacit knowledge is obtained from the jokes. With a large and diverse enough group of participants across games, a variety of tacit knowledge can be extracted.