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Richard GonzalezRichard Gonzalez

Center Director, Research Center for Group Dynamics, Institute for Social Research
Director, BioSocial Methods Collaborative, RCGD
Amos N Tversky Collegiate Professor, Psychology and Statistics, LSA
Professor of Marketing, Stephen M Ross School of Business
Professor of Integrative Systems and Design, College of Engineering

 

E-mail: Email Richard Gonzalez
Address: Research Center for Group Dynamics
Institute for Social Research
University of Michigan
426 Thompson Street
Ann Arbor, Michigan 48106
Phone: 734-647-6785

Examining similarity asymmetries in judgment of perceptual stimuli

Sep 17, 2011 | Decision Making, Psychology

This work extends Tversky’s features of similarity model to judgments of color and propose a computation model for the key empirical result.

Polk, T. A., Behensky, C., Gonzalez, R., & Smith, E. (2002). Rating the similarity of simple perceptual stimuli: Asymmetries induced by manipulating exposure frequency. Cognition, 82, B75-B88. doi:10.1016/S0010-0277(01)00151-2 (PDF)

Abstract

When judging the similarity of two stimuli, people’s ratings often differ depending on the order in which the comparison is presented (A vs. B or B vs. A). Such directional asymmetries have typically been demonstrated using complex concepts that have a large number of semantic features and a standard explanation is that different sets of features are emphasized depending on the direction of the comparison. In this study, we show that directional asymmetries in the similarity of simple perceptual stimuli can be predictably manipulated merely by presenting each member of a pair with different frequency. Participants rated the similarity of color patches before and after performing an irrelevant training task in which a subset of colors was presented ten times more frequently than others. The similarity ratings after training were significantly more asymmetric than the ratings before training. We discuss the implications of these findings for models of similarity judgment and propose a computationally explicit explanation based on asymmetries in representational stability.