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Related Experiment Video

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Creating Virtual-hand and Virtual-face Illusions to Investigate Self-representation
06:53

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Published on: March 1, 2017

The face in the crowd effect: anger superiority when using real faces and multiple identities.

Amy E Pinkham1, Mark Griffin, Robert Baron

  • 1Department of Psychiatry, University of Pennsylvania, PA, USA. apinkham@mail.smu.edu

Emotion (Washington, D.C.)
|February 10, 2010
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Summary

The face in the crowd effect shows angry faces are found faster than happy ones. This study confirms this effect with real faces in realistic crowds, proving its natural occurrence.

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Area of Science:

  • Cognitive Psychology
  • Social Psychology
  • Visual Perception

Background:

  • The face in the crowd effect demonstrates faster detection of threatening (angry) faces among distractors compared to non-threatening (happy) faces.
  • Previous research relied heavily on schematic stimuli, with inconsistent results when applying the effect to real human faces, questioning its ecological validity.

Purpose of the Study:

  • To investigate the face in the crowd effect using veridical (real) faces within heterogeneous crowds.
  • To determine if the effect holds true under more ecologically valid conditions than previously studied.

Main Methods:

  • A visual search paradigm was employed.
  • Veridical faces with prototypical emotional expressions (angry, happy, neutral) were presented in crowds of distractor faces.
  • Search speed and accuracy were measured.

Main Results:

  • Angry faces were detected significantly faster and more accurately than happy faces.
  • This effect was observed in crowds composed of both neutral and emotional distractors.
  • The findings extend the face in the crowd effect beyond homogenous crowds.

Conclusions:

  • The study provides the first evidence extending the face in the crowd effect to heterogeneous, realistic crowds.
  • The results validate the face in the crowd effect as a naturalistic phenomenon with real-world applicability.
  • Threat detection via facial expression is robust even in complex visual environments.