Disappeared or deleted? Media coverage of policy content in presidential debates

Abstract While it is widely accepted that watching televised presidential debates helps voters stay informed about candidates and campaign issues, voters are increasingly turning to the media to learn about televised debates rather than watching them directly. Coupled with this trend is growing criticisms over presidential debates’ focus on negative attacks on opponents at the expense of policy discussions. We examine whether media outlets systematically bias the content of presidential debates, potentially amplifying their perceived negativity in presidential debates. Specifically, we theorize that the media outlets overemphasize non-policy aspects of presidential debates, because such coverage can help them draw viewer attention and is perceived to have greater news value. We further expect the continued exposure to media coverage of debates to weaken policy-related considerations in voters’ decision-making. We test these theoretical expectations using the case of the 2022 presidential election in South Korea. Using keyword-assisted topic model (keyATM), we first compare candidates’ speeches during the presidential debates with newspaper coverage of the debates. We find that non-policy topics, including personal attacks on the opponent and scandals, appeared more frequently in the newspaper coverage than in the actual debates. Next, we show that the continued exposure to media’s election coverage can reinforce voters’ tendency to base their voting decisions on non-policy issues through post-election survey data. Our findings offer significant insights into understanding media campaign coverage and its electoral significance in today’s media environment.

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Publication Details

Journal
Japanese Journal of Political Science
Published
2025-12-01
DOI
https://doi.org/10.1017/s1468109925100169
Primary Topic
Computational and Text Analysis Methods
Type
article
Field-Weighted Citation Impact
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article

Disappeared or deleted? Media coverage of policy content in presidential debates

Sin-Jae Kang, Jiyoung Park, Jeong Hyun Kim
Japanese Journal of Political Science
Computational and Text Analysis Methods
article

Disappeared or deleted? Media coverage of policy content in presidential debates

Sin-Jae Kang, Jiyoung Park, Jeong Hyun Kim
article en

Abstract

Abstract While it is widely accepted that watching televised presidential debates helps voters stay informed about candidates and campaign issues, voters are increasingly turning to the media to learn about televised debates rather than watching them directly. Coupled with this trend is growing criticisms over presidential debates’ focus on negative attacks on opponents at the expense of policy discussions. We examine whether media outlets systematically bias the content of presidential debates, potentially amplifying their perceived negativity in presidential debates. Specifically, we theorize that the media outlets overemphasize non-policy aspects of presidential debates, because such coverage can help them draw viewer attention and is perceived to have greater news value. We further expect the continued exposure to media coverage of debates to weaken policy-related considerations in voters’ decision-making. We test these theoretical expectations using the case of the 2022 presidential election in South Korea. Using keyword-assisted topic model (keyATM), we first compare candidates’ speeches during the presidential debates with newspaper coverage of the debates. We find that non-policy topics, including personal attacks on the opponent and scandals, appeared more frequently in the newspaper coverage than in the actual debates. Next, we show that the continued exposure to media’s election coverage can reinforce voters’ tendency to base their voting decisions on non-policy issues through post-election survey data. Our findings offer significant insights into understanding media campaign coverage and its electoral significance in today’s media environment.

Japanese Journal of Political ScienceVol. 26(4)
Yonsei University (KR)
Openalex Percentile: Top 50%
Computational and Text Analysis Methods
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