Reverse Correlating Social Face Perception

Ron Dotsch*, Alexander Todorov

*Corresponding author for this work

Research output: Contribution to journalArticleAcademicpeer-review

Abstract

Reverse correlation (RC) techniques provide a data-driven approach to model internal representations in an unconstrained way. Here, we used this approach to model social perception of faces. In the RC task, participants repeatedly selected from two face images-created by superimposing randomly generated noise masks on the same face-the face that looked most trustworthy (or, in other conditions: untrustworthy, dominant, or submissive). We calculated classification images (CIs) by averaging all selected images. Trait judgments of independent participants, as well as objective metrics, showed that the CIs visualized the intended traits well. Furthermore, tests of pixel clusters showed that diagnostic information resided mostly in mouth, eye, eyebrow, and hair regions. The current work shows that RC provides an excellent tool to extract psychologically meaningful images that map onto social perception.

Original languageEnglish
Pages (from-to)562-571
Number of pages10
JournalSocial Psychological and Personality Science
Volume3
Issue number5
DOIs
Publication statusPublished - Sept 2012

Keywords

  • facial expressions
  • measurement
  • person perception
  • social cognition
  • social judgment

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