Behind the Third-Person Effect: Differentiating Perceptual Processes for Self and Other

  1. Douglas M. McLeod1,
  2. Benjamin H. Detenber2,
  3. William P. Eveland Jr.3

Article first published online: 10 JAN 2006

DOI: 10.1111/j.1460-2466.2001.tb02902.x

Issue

Journal of Communication

Journal of Communication

Volume 51, Issue 4, pages 678–695, December 2001

Additional Information

How to Cite

McLeod, D. M., Detenber, B. H. and Eveland, W. P. (2001), Behind the Third-Person Effect: Differentiating Perceptual Processes for Self and Other. Journal of Communication, 51: 678–695. doi: 10.1111/j.1460-2466.2001.tb02902.x

Author Information

  1. 1

    Douglas M. McLeod (PhD, University of Minnesota) is a professor of journalism and mass communication at the University of Wisconsin, Madison.

  2. 2

    Benjamin H. Detenber (PhD, Stanford) is an associate professor in the School of Communication Studies at Nanyang Technological University, Singapore.

  3. 3

    William P. Eveland, Jr. (PhD, University of Wisconsin, Madison) is an assistant professor at The Ohio State University.

*Address correspondence to this address or send email tocrberger@ucdavis.edu.

Publication History

  1. Issue published online: 10 JAN 2006
  2. Article first published online: 10 JAN 2006

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This study investigated factors related to two types of judgments that make up the third-person perception: media effects on others and effects on self. Specifically, separate regression path models revealed that estimates of effects on others are based on a relatively naive schema for media effects that is similar to the “magic bullet” model of media effects (i.e., more exposure leads to greater effects). On the other hand, assessing effects on self involves a more complex, conditional effects model. The different pattern of results for the self and other models reflect the “fundamental attribution error” from attribution theory. The path models also extend results from the perceptual component to the behavioral component of the third-person effect by linking the explanatory variables to support for censorship. Both models showed that paternalistic attitudes were the strongest predictor of support for censorship.

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