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Gaffes Over Policy: New Field Experiment Uncovers Distinct Motivations for Selective Exposure in Elections
Insights from the Field
gaffe appeal
partisan media
selective exposure
field experiment
Political Behavior
PSR&M
4 Stata files
7 datasets
4 text files
2 PDF files
1 other files
Dataverse
Gaffe Appeal: A Field Experiment on Partisan Selective Exposure to Election Messages was authored by Timothy Ryan and Ted Brader. It was published by Cambridge in PSR&M in 2017.

The media landscape's evolution has amplified concerns about citizens' biased news consumption.

In political science, the idea that voters gravitate toward information matching their views is a cornerstone concept. However, existing evidence presents notable challenges in definitively confirming its prevalence across all contexts.

Researchers grappled with inherent tensions: balancing artificial lab environments against real-world complexities where confounding factors are difficult to separate. Our innovative field experiment approach in the United States offers clearer insights into voter information-seeking behaviors by navigating these methodological dilemmas.

Key Findings & Methodology

Our research reveals that partisan selective exposure isn't uniform - it's driven by two distinct motivations:

  • Voters show consistent preference for ideologically aligned political messaging
  • A surprising finding emerges: attention to candidate gaffes (mistakes) is significantly influenced by partisan identity, not just policy differences

Contribution & Significance

Our findings illuminate the underpinnings of campaign media focus on trivial errors:

• Contrary to expectations, voters actively seek out information about candidate miscues regardless of their political leanings

• This discovery helps explain why election coverage often emphasizes personality flaws over substantive policy debates 📊

The results strengthen our understanding of how partisanship shapes political communication consumption patterns in the digital age.

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Political Science Research & Methods
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