Abstract
Electoral campaigns are the foundation of democratic governance; yet scholarship on the content of campaign communications remains underdeveloped. In this paper, we advance research on U.S. congressional campaigns by integrating and extending extant theories of campaign communication. We test the resulting predictions with a novel dataset based on candidate Web sites over three election cycles. Unlike television advertisements or newspaper coverage, Web sites provide an unmediated, holistic, and representative portrait of campaigns. We find that incumbents and challengers differ across a broad range of behavior that reflects varying attitudes toward risk, that incumbents strategies depend on the competitiveness of the race, and that candidates link negative campaigning to other aspects of their rhetorical strategies. Our efforts provide researchers with a basis for moving toward a more complete understanding of congressional campaigns.
Original language | English (US) |
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Pages (from-to) | 343-366 |
Number of pages | 24 |
Journal | American Political Science Review |
Volume | 103 |
Issue number | 3 |
DOIs | |
State | Published - Aug 2009 |
Funding
We thank Nora Paul and Brian Southwell for critical guidance in constructing our original coding framework, Gary Jacobson for providing candidate background data, and the dozens of individuals who assisted in data collection. We also thank Lonna Atkeson, Amber Wichowsky, and many others for providing advice. We owe a special debt of gratitude to the APSR’s reviewers and editors for insightful guidance that fundamentally shaped all aspects of the paper. Support for this research was provided by the University of Minnesota McKnight Land-Grant Professorship, Northwestern University’s AT&T Research Scholar Fund, and, for the survey of website designers, the National Science Foundation (SES-0822819 and SES-0822819). Authors’ names are listed in alphabetical order.
ASJC Scopus subject areas
- Sociology and Political Science
- Political Science and International Relations