Document Type

Dissertation

Degree

Doctor of Philosophy

Major

Political Science, American Politics

Date of Defense

9-21-2017

Graduate Advisor

David B Robertson

Committee

David B Robertson

David C Kimball

Jason Gainous

Adriano Udani

Abstract

Political polarization is a defining feature of the contemporary American political landscape. While there is little doubt that elite polarization levels have risen dramatically in recent decades, there is some debate over the existence of a corresponding rise in mass polarization. Recent scholarship on mass polarization has cited evidence related to citizens’ positions on public policy issues, party sorting, and geographic polarization; however, questions remain as to the nature and extent of mass polarization in online spaces. Specifically, more needs to be known regarding how expressions of elite polarization influence the formation of polarized communities within social media.

This dissertation examines the question: Does elite polarization contribute to mass polarization in social media? This question is approached in three stages. First, this dissertation tests whether or not a causal link between elite and mass polarization strengthens with temporal proximity to highly politicized and potentially polarizing events over the span of the 2016 Republican presidential primary. Second, this dissertation examines the instant effects of elite polarization by examining a minute-by-minute live stream of reactions on Twitter during the first 2016 presidential debate. Third, this dissertation tests a contemporary theory which claims a presidential candidate’s patterns of speech sows the seeds of mass polarization in the form of resentment, fear, or incivility.

This dissertation also employs the use of network analysis tools to measure the extent to which polarized communities form on social media in response to elite cues. The nature of such causal relationships provides insight into the influence polarizing messages by elites may have on mass polarization while taking into consideration the unique characteristics of the social media communications environment. In doing so, this dissertation offers a blueprint for future researchers who seek to better understand how networked technologies shape human interactions.

OCLC Number

1037018575

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