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The inference of emotions by a probabilistic programming language account for both the overall emotional responses and individual emotions for different outcomes.

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

The inference of emotions by a probabilistic programming language account for both the overall emotional responses and individual emotions for different outcomes. Bayesian models have been built for 8 different emotion category according to financial reward won from a wheel spinning game.

This work is a part of the graduation requirement from Cognitive Science master's program. Full graduation project can be found [here] (https://hdl.handle.net/11511/108247)

Dataset is taken from Ong, D. C., Zaki, J., & Goodman, N. D. (2015). Affective cognition: Exploring lay theories of emotion. Cognition, 143, 141-162.

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The inference of emotions by a probabilistic programming language account for both the overall emotional responses and individual emotions for different outcomes.

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