Discursive power in the coverage of Covid-19: An international comparison of hidden structures in contemporary media systems identified with deep learning techniques in text, images, and video (additional Corona-related funding)

Grant number: unknown

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Key facts

  • Disease

    COVID-19
  • Funder

    Volkswagen Stiftung
  • Principal Investigator

    Prof Dr and Dr and Prof Dr Andreas Jungherr, Jisun An, Oliver Posegga
  • Research Location

    Germany, United Kingdom
  • Lead Research Institution

    Universität Konstanz
  • Research Priority Alignment

    N/A
  • Research Category

    Policies for public health, disease control & community resilience

  • Research Subcategory

    Communication

  • Special Interest Tags

    N/A

  • Study Type

    Non-Clinical

  • Clinical Trial Details

    N/A

  • Broad Policy Alignment

    Pending

  • Age Group

    Unspecified

  • Vulnerable Population

    Unspecified

  • Occupations of Interest

    Unspecified

Abstract

The current project "Communicative Power in Hybrid Media Systems" identifies biases driven by commercial or political foundations of specific media organizations as well as the hidden structural power-relationships between different media outlets and types and the interconnection with alternative media and publics on social media. What determines the coverage of Covid-19 and related political contestation in traditional and new media? The additional module will provide an important contribution in understanding the role of media coverage and social media reactions in the Corona crisis in international comparison. The project will identify hidden power structures between media organizations in contemporary hybrid media systems. This will provide insights about the determinants of information quality and the spread of misinformation during a large social crisis in media coverage. The project team will analyze media coverage on Corona in international comparison between Germany, UK, USA, and South Korea by using computational social science methods.