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Quality & Quantity

05.02.2025

Applying semantic network analysis to explore the relationship between media ideology and editorial coverage of COVID-19

verfasst von: Sejung Park, Nisha Sridharan, K. Hazel Kwon

Erschienen in: Quality & Quantity

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Abstract

This study investigated how U.S. newspaper editorials established their editorial foci on the coronavirus pandemic, and how they differed according to newspapers’ political ideology. Guided by indexing theory, this study analyzed 584 editorials published in the top 50 U.S. newspapers between March and May 2020 using semantic network analysis and statistical analysis. This study reveals four overarching thematic attributes prevalent in the editorials: federal medical response, local government response, economic impact, and personal livelihood. The editorials focused predominantly on the government’s response to the pandemic, followed by its economic impact, confirming the process of indexing in the editorials. Additionally, Democratic newspapers provided more editorials within these themes than neutral and Republican-leaning ones.

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For legibility, we used the original form of words in reporting our results instead of stemmed forms.

Of the 50 newspapers, 6 did not endorse any candidates from 1980 to 2020. In addition, the SFGate was merged into the SF Chronicle and then unmerged, and we used both endorsements.

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Titel: Applying semantic network analysis to explore the relationship between media ideology and editorial coverage of COVID-19
verfasst von: Sejung Park
Nisha Sridharan
K. Hazel Kwon
Publikationsdatum: 05.02.2025
Verlag: Springer Netherlands
Erschienen in: Quality & Quantity
Print ISSN: 0033-5177
Elektronische ISSN: 1573-7845
DOI: https://doi.org/10.1007/s11135-025-02065-2