Digital news media as a social resilience proxy: A computational political economy perspective

Abstract

This article investigates how the COVID-19 pandemic was framed in public, private and non-profit media production. It conceptualises digital news as an indicator of social resilience and the interaction between social and biological/natural systems. We analysed news articles published in 2020/2021 on 21 Croatian websites using natural language processing. We collected 985,850 articles and manually coded samples to train different classifiers. The first classifier was developed to determine which articles relate to COVID-19. The second classifier was used for articles' topic classification; the third classifier was used to classify articles into resilience classes. A limited discussion of transformative (long-term) resilience, especially in private media, contributed to the most significant content share. The debate focused on keeping the status quo through coping or returning to pre-pandemic conditions through adaptive mechanisms. The news media contributed to how public issues were framed and how science and scientific research were discussed.