From Cognitive to Computational Modeling: Text-based Risky Decision-Making Guided by Fuzzy Trace Theory

• URL: http://arxiv.org/abs/2205.07164v1
• Date: Sun, 15 May 2022 02:25:28 GMT
• Title: From Cognitive to Computational Modeling: Text-based Risky Decision-Making Guided by Fuzzy Trace Theory
• Authors: Jaron Mar and Jiamou Liu
• Abstract summary: Fuzzy trace theory (FTT) is a powerful paradigm that explains human decision-making by incorporating gists. We propose a computational framework which combines the effects of the underlying semantics and sentiments on text-based decision-making. In particular, we introduce Category-2- to learn categorical gists and categorical sentiments, and demonstrate how our computational model can be optimised to predict risky decision-making in groups and individuals.
• Score: 5.154015755506085
• License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
• Abstract: Understanding, modelling and predicting human risky decision-making is challenging due to intrinsic individual differences and irrationality. Fuzzy trace theory (FTT) is a powerful paradigm that explains human decision-making by incorporating gists, i.e., fuzzy representations of information which capture only its quintessential meaning. Inspired by Broniatowski and Reyna's FTT cognitive model, we propose a computational framework which combines the effects of the underlying semantics and sentiments on text-based decision-making. In particular, we introduce Category-2-Vector to learn categorical gists and categorical sentiments, and demonstrate how our computational model can be optimised to predict risky decision-making in groups and individuals.

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