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Investigating Perceptual Biases in Icon Arrays

Cindy Xiong, Ali Sarvghad, Daniel G. Goldstein, Jake M. Hofman, Çağatay Demiralp

2022CHI Conference on Human Factors in Computing Systems37 citationsDOIOpen Access PDF

Abstract

Icon arrays are graphical displays in which a subset of identical shapes are filled to convey probabilities. They are widely used for communicating probabilities to the general public. A primary design decision concerning icon arrays is how to fill and arrange these shapes. For example, a designer could fill the shapes from top to bottom or in a random fashion. We investigated the effect of different arrangements in icon arrays on probability perception. We showed participants icon arrays depicting probabilities between 0% and 100% in six different arrangements. Participants were more accurate in estimating probabilities when viewing the top, row, and diagonal arrangements, but they overestimated the proportions with the central arrangement and underestimated the proportions with the edge arrangement. They were biased to either overestimate or underestimate when viewing the random arrangement depending on the objective proportions, following a cyclical pattern consistent with existing findings in the psychophysics literature.

Topics & Concepts

IconDiagonalPerceptionComputer sciencePsychophysicsArtificial intelligenceEnhanced Data Rates for GSM EvolutionPattern recognition (psychology)Computer visionMathematicsPsychologyGeometryProgramming languageNeuroscienceData Visualization and AnalyticsMultisensory perception and integrationSensory Analysis and Statistical Methods
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