Investigating Emotions over the Monetary Outcomes of Wheel-Spin Game using Bayesian Models

Date

2024-1-19

Author

Arıcı, İrem

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This study investigates the relationship between emotions and outcomes of wheel-spin game with monetary reward. The inference of emotions by a probabilistic programming language account for both the overall emotional responses and individual emotions for different outcomes. The study examined previously published data with Bayesian models. With different probabilities of winning for each outcome, the emotional reaction for the amount received and the pointer position on the outcome slice are included in the models. The findings conclude that, although the positional inferences have failed, they feel less surprised in the event of high probability win and while players experience more positive emotions as the amount of monetary outcome increases, their negative emotional responses decrease.

Subject Keywords

emotion inference, affective cognition, appraisal theory of emotion, prediction

URI

https://hdl.handle.net/11511/108247

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Graduate School of Informatics, Term Project