Examining U.S. Newspapers’ Partisan Bias in COVID-19 News Using Computational Methods

Research output: Contribution to journalArticlepeer-review

4 Scopus citations

Abstract

The COVID-19 pandemic has become a partisan political issue instead of purely a public health issue in the U.S. Partisan media bias leads to conflicting messages and drastic differences in preventive behaviors and risk perceptions between Democrats and Republicans. Guided by partisan media bias literature and framing theory, this study examined partisan media bias in the U.S. national and local newspapers regarding COVID-19 using computational methods. It visualized the trends of COVID-19 news articles published by left-leaning, least biased, and right-leaning media as well as revealed frames that were used in partisan media to report COVID-19. Findings demonstrated that partisan media covered certain COVID-19 frames more frequently than others. Even though left-leaning, least biased, and right-leaning media did not differ in the likelihood of publishing COVID-19 articles and they did not publish a significantly different number of COVID-19 articles, partisan media used each COVID-19 frame significantly differently. Specifically, least biased media was more likely than left-leaning media and right-leaning media to discuss the stay-at-home order. Other frames were not significantly differently applied by different partisan media. Implications for COVID-19 news reporting and message design as well as the lessons for politics and health policy are provided.

Original languageEnglish (US)
Pages (from-to)78-96
Number of pages19
JournalCommunication Studies
Volume74
Issue number1
DOIs
StatePublished - 2023

Keywords

  • COVID-19
  • Computational methods
  • Framing
  • Media bias
  • Partisan bias

ASJC Scopus subject areas

  • Communication

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