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Gaffe Appeal A Field Experiment on Partisan Selective Exposure to Election Messages*
Published online by Cambridge University Press: 20 November 2015
Abstract
The possibility that citizens expose themselves to information in biased ways—so-called selective exposure—has acquired new importance as the media environment has evolved to provide more choices concerning what to watch and read. But evidence for the most prominent idea in selective exposure research—that citizens prefer attitude-consistent information—is notably mixed. Methodological challenges likely contribute to the inconclusive nature of findings, as researchers face trade-offs between the artificiality of lab environments and the difficult-to-disentangle confounds of observational analysis. We improve understanding of selective exposure in two ways. First, we consider how message aspects other than attitude-consistency affect exposure decisions. Second, we study selective exposure with an innovative field experiment conducted in the United States that addresses limitations of other approaches. Our results allow us to reach more confident conclusions about the prevalence of motivated selective exposure, and help to illuminate underpinnings of the oft-lamented tendency for campaign media to focus on candidate miscues rather than substantive policy differences.
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- Original Articles
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- Copyright
- © The European Political Science Association 2015
Footnotes
Timothy J. Ryan is an Assistant Professor of Political Science, Department of Political Science, 361 Hamilton Hall, The University of North Carolina at Chapel Hill, Chapel Hill, NC 27599-3265 ([email protected]). Ted Brader is a Professor of Political Science, Department of Political Science, 5700 Haven Hall, University of Michigan, 505 S. State St., Ann Arbor, MI 48109-1045 ([email protected]). We are thankful to David Broockman and Donald Green for comments on an earlier draft, though errors are our own. To view supplementary material for this article, please visit http://dx.doi.org/10.1017/psrm.2015.62
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