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From Cognitive to Computational Modeling: Text-based Risky Decision-Making Guided by Fuzzy Trace Theory
- Source :
- Findings of the Association for Computational Linguistics: NAACL (2022) 391-409
- Publication Year :
- 2022
-
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.
Details
- Database :
- arXiv
- Journal :
- Findings of the Association for Computational Linguistics: NAACL (2022) 391-409
- Publication Type :
- Report
- Accession number :
- edsarx.2205.07164
- Document Type :
- Working Paper
- Full Text :
- https://doi.org/10.18653/v1/2022.findings-naacl.30