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Mobilizing Voters with Aggressive Metaphors

Published online by Cambridge University Press:  25 October 2017

Nathan P. Kalmoe
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Abstract

How do personality traits condition the effects of campaign messages meant to mobilize voters? With two nationally representative US survey experiments, I show that common aggressive metaphors mobilize or demobilize voters depending on their traits. Aggressive metaphors increase the mobilizing impact of motivations to participate among aggressive individuals but decrease that impact among low-aggression people. For example, the language mobilizes strong partisans with aggressive personalities but demobilizes strong partisans low in aggression. This heterogeneity showcases the nuanced power of metaphors in campaigns, reaffirms the importance of personality in political behavior, and reveals the hidden role of aggression in non-violent political behavior for the first time. In practice, the net effects of aggressive metaphors can be positive, negative, or null depending on average traits in an audience.

Type
Original Articles
Information
Political Science Research and Methods , Volume 7 , Issue 3 , July 2019 , pp. 411 - 429
Copyright
© The European Political Science Association 2017 

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Footnotes

*

Nathan Kalmoe is an Assistant Professor of Political Communication at Louisiana State University, Journalism Building, Baton Rouge, LA 70803 (nkalmoe@lsu.edu). This project was supported by the Gerald R. Ford Fellowship and the Marsh Research Fellowship at the University of Michigan. Data for Study 2 were collected by Time-Sharing Experiments for the Social Sciences, NSF Grant 0818839, Jeremy Freese and Penny Visser, Principal Investigators. The author thanks Don Kinder, Ted Brader, Nancy Burns, Nick Valentino, Brad Bushman, Jenna Bednar, Cindy Kam, Charles Doriean, Josh Gubler, anonymous reviewers, and the participants of the Interdisciplinary Workshop on Politics and Policy at the University of Michigan for their comments and suggestions. An earlier version of this work was presented at the 2011 APSA Annual Meeting. To view supplementary material for this article, please visit https://doi.org/10.1017/psrm.2017.36

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Kalmoe Dataset

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