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The biological roots of political extremism

Negativity bias, political ideology, and preferences for political news

Published online by Cambridge University Press:  27 December 2017

Justin Robert Keene ,
Heather Shoenberger ,
Collin K. Berke  and
Paul D. Bolls
Justin Robert Keene*
Affiliation:
Texas Tech University
Heather Shoenberger
Affiliation:
University of Oregon
Collin K. Berke
Affiliation:
University of Nebraska–Lincoln
Paul D. Bolls
Affiliation:
Texas Tech University
*
Correspondence: Justin Robert Keene, Department of Journalism & Electronic Media, College of Media and Communication, Texas Tech University, 3003 15th Street, Lubbock, TX 79409 USA. Email: [email protected]
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Abstract

Recent research has revealed the complex origins of political identification and the possible effects of this identification on social and political behavior. This article reports the results of a structural equation analysis of national survey data that attempts to replicate the finding that an individual’s negativity bias predicts conservative ideology. The analysis employs the Motivational Activation Measure (MAM) as an index of an individual’s positivity offset and negativity bias. In addition, information-seeking behavior is assessed in relation to traditional and interactive media sources of political information. Results show that although MAM does not consistently predict political identification, it can be used to predict extremeness of political views. Specifically, high negativity bias was associated with extreme conservatism, whereas low negativity bias was associated with extreme liberalism. In addition, political identification was found to moderate the relationship between motivational traits and information-seeking behavior.

Keywords

Political orientationmotivational activationinformation selectionpolitical ideologyapproach system activationdefensive system activation
Type
Articles
Information
Politics and the Life Sciences , Volume 36 , Issue 2 , Fall 2017 , pp. 37 - 48
Copyright
© Association for Politics and the Life Sciences 2017 

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