Exploring the Value of Computational Methods for Metajournalistic Discourse: The Example of COVID-19 Reporting in Dutch Newspapers

Abstract

The COVID-19 pandemic raised questions about trust in journalism and the quality of news reporting during societal crises. While journalists and media professionals frequently offered critical reflections based on personal experiences and observations, computational methods are not widely used to support these evaluative processes. We aim to extend the conversation on metajournalistic discourse by considering the inclusion of empirical methods for monitoring journalistic practices. By disclosing our findings about Dutch news media’s corona reporting between 2019 and 2022, we demonstrate how computational methods for content analyses of news texts can yield empirically informed insights into different facets of journalistic performance. The corpus includes 106,616 corona-related articles from national and regional newspapers in the Netherlands. We deployed text analytical methods such as topic modelling and named entity recognition to explore Dutch corona reporting in respect to different normative criteria (informing, monitoring, offering platforms for discussion and opinion, interpretation, analysis, and setting public agendas). The study was requested by a large Dutch newspaper to receive a systematic-empirical analysis of journalistic practice for self-evaluation. We argue that computational methods combined with qualitative analyses can stimulate dialogue and critical reflection among news media professionals.