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Censorship or self-control? Hate speech, the state and the voter in the Kenyan election of 2013*

Published online by Cambridge University Press:  28 July 2016

Warigia M. Bowman*
Affiliation:
University of Arkansas, Clinton School of Public Service, 1200 President Clinton Avenue, Little Rock, AR 72201, USA
J. David Bowman*
Affiliation:
Physics Division, Oak Ridge National Laboratory, Oak Ridge, TN, USA
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Abstract

In 2013, the Kenyan government adopted a hybrid censorship strategy that relied on regulation, the presence of a strong security state, and the willingness of Kenyans to self-censor. The goal of this censorship strategy was to ensure a peaceful election. This study examines two issues. First, it investigates steps taken by the Kenyan government to minimise hate speech. Second, it explores how efforts to minimise hate speech affected citizen communications over SMS during the 2013 election. An initial round of qualitative data was gathered (n = 101) through a structured exit interview administered election week. A statistically significant, representative sample of quantitative data was gathered by a reputable Kenyan polling firm (n ≥ 2000). Both sets of empirical data indicate that Kenyan citizens cooperated in large part with efforts to limit political speech. Yet speech was not always completely “peaceful’. Rather, voters used electronic media to insult, offend, and express contentious political views as well as express peace speech. This study argues that the empirical evidence suggests hate speech over text messages during the Kenyan election declined between 2008 and 2013.”

Information

Type
Research Article
Copyright
Copyright © Cambridge University Press 2016 
Figure 0

Table IData Sources Used in Analysis

Figure 1

Table IIContent of election related text messages received on election day

Figure 2

Table IIIDifferences between selected responses based on rural or urban residence

Figure 3

Table IVDifferences Between Selected Responses Based on Region*

Figure 4

Table VDifferences in reports of messages received based on ethnicity