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

Sejung Park (), Nisha Sridharan and K. Hazel Kwon
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Sejung Park: Pukyong National University
Nisha Sridharan: Temple University
K. Hazel Kwon: Arizona State University

Quality & Quantity: International Journal of Methodology, 2025, vol. 59, issue 2, No 22, 1283-1303

Abstract: 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.

Keywords: Media ideology; Newspaper editorials; COVID-19; Crisis communication; Indexing theory; Semantic network analysis (search for similar items in EconPapers)
Date: 2025
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DOI: 10.1007/s11135-025-02065-2

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