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Title: Your gameplay says it all : modelling motivation in Tom Clancy's The Division
Authors: Melhart, David
Azadvar, Ahmad
Canossa, Alessandro
Liapis, Antonios
Yannakakis, Georgios N.
Keywords: Computer games -- Design
Computer games -- Psychological aspects
Computer games -- Social aspects
Level design (Computer science)
Issue Date: 2019
Publisher: Institute of Electrical and Electronics Engineers
Citation: Melhart, D., Azadvar, A., Canossa, A., Liapis, A., & Yannakakis, G. N. (2019). Your gameplay says it all : modelling motivation in Tom Clancy's The Division. Proceedings of the IEEE Conference on Games, London.
Abstract: Is it possible to predict the motivation of players just by observing their gameplay data? Even if so, how should we measure motivation in the first place? To address the above questions, on the one end, we collect a large dataset of gameplay data from players of the popular game Tom Clancy’s The Division. On the other end, we ask them to report their levels of competence, autonomy, relatedness and presence using the Ubisoft Perceived Experience Questionnaire. After processing the survey responses in an ordinal fashion we employ preference learning methods based on support vector machines to infer the mapping between gameplay and the reported four motivation factors. Our key findings suggest that gameplay features are strong predictors of player motivation as the best obtained models reach accuracies of near certainty, from 92% up to 94% on unseen players.
Appears in Collections:Scholarly Works - InsDG

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