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Using Resource-Rational Analysis to Understand Cognitive Biases in Interactive Data Visualizations

Human-Computer Interaction 2020-10-01 v2

Abstract

Cognitive biases are systematic errors in judgment. Researchers in data visualizations have explored whether cognitive biases transfer to decision-making tasks with interactive data visualizations. At the same time, cognitive scientists have reinterpreted cognitive biases as the product of resource-rational strategies under finite time and computational costs. In this paper, we argue for the integration of resource-rational analysis through constrained Bayesian cognitive modeling to understand cognitive biases in data visualizations. The benefit would be a more realistic "bounded rationality" representation of data visualization users and provides a research roadmap for studying cognitive biases in data visualizations through a feedback loop between future experiments and theory

Keywords

Cite

@article{arxiv.2009.13368,
  title  = {Using Resource-Rational Analysis to Understand Cognitive Biases in Interactive Data Visualizations},
  author = {Ryan Wesslen and Doug Markant and Alireza Karduni and Wenwen Dou},
  journal= {arXiv preprint arXiv:2009.13368},
  year   = {2020}
}

Comments

IEEE VIS 2020 Workshop on Visualization Psychology (VisPsych)

R2 v1 2026-06-23T18:50:58.482Z