IDEAS home Printed from https://ideas.repec.org/a/spr/qualqt/v59y2025i2d10.1007_s11135-025-02065-2.html
   My bibliography  Save this article

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

Author

Listed:
  • Sejung Park

    (Pukyong National University)

  • Nisha Sridharan

    (Temple University)

  • K. Hazel Kwon

    (Arizona State University)

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.

Suggested Citation

  • Sejung Park & Nisha Sridharan & K. Hazel Kwon, 2025. "Applying semantic network analysis to explore the relationship between media ideology and editorial coverage of COVID-19," Quality & Quantity: International Journal of Methodology, Springer, vol. 59(2), pages 1283-1303, April.
    • Handle: RePEc:spr:qualqt:v:59:y:2025:i:2:d:10.1007_s11135-025-02065-2
    DOI: 10.1007/s11135-025-02065-2
    as

    Download full text from publisher

    File URL: http://link.springer.com/10.1007/s11135-025-02065-2
    File Function: Abstract
    Download Restriction: Access to the full text of the articles in this series is restricted.
    File URL: https://libkey.io/10.1007/s11135-025-02065-2?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:spr:qualqt:v:59:y:2025:i:2:d:10.1007_s11135-025-02065-2. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    We have no bibliographic references for this item. You can help adding them by using this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.springer.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.