From Cognitive to Computational Modeling: Text-based Risky Decision-Making Guided by Fuzzy Trace Theory
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.
Cite
@article{arxiv.2205.07164,
title = {From Cognitive to Computational Modeling: Text-based Risky Decision-Making Guided by Fuzzy Trace Theory},
author = {Jaron Mar and Jiamou Liu},
journal= {arXiv preprint arXiv:2205.07164},
year = {2022}
}