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How government-controlled media shifts policy attitudes through framing

Published online by Cambridge University Press:  21 July 2021

Jennifer Pan Open the ORCID record for Jennifer Pan [Opens in a new window] ,
Zijie Shao Open the ORCID record for Zijie Shao [Opens in a new window]  and
Yiqing Xu
Jennifer Pan
Affiliation:
Department of Communication, Stanford University, Stanford, CA, USA
Zijie Shao*
Affiliation:
School of Government and Public Affairs, Communication University of China, Beijing, China
Yiqing Xu
Affiliation:
Department of Political Science, Stanford University, Stanford, CA, USA
*
*Corresponding author. Email: [email protected]
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Abstract

Research shows that government-controlled media is an effective tool for authoritarian regimes to shape public opinion. Does government-controlled media remain effective when it is required to support changes in positions that autocrats take on issues? Existing theories do not provide a clear answer to this question, but we often observe authoritarian governments using government media to frame policies in new ways when significant changes in policy positions are required. By conducting an experiment that exposes respondents to government-controlled media—in the form of TV news segments—on issues where the regime substantially changed its policy positions, we find that by framing the same issue differently, government-controlled media moves respondents to adopt policy positions closer to the ones espoused by the regime regardless of individual predisposition. This result holds for domestic and foreign policy issues, for direct and composite measures of attitudes, and persists up to 48 hours after exposure.

Keywords

Chinaexperimentframingmediapolicy changepublic opinion
Type
Original Article
Information
Political Science Research and Methods , Volume 10 , Issue 2 , April 2022 , pp. 317 - 332
Copyright
Copyright © The Author(s), 2021. Published by Cambridge University Press on behalf of the European Political Science Association

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Supplementary material: Link

Pan et al. Dataset

Dataset

https://doi.org/10.7910/DVN/LBLOVK
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Pan et al. supplementary material

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