Abstract
Over the past decade, data journalism has received considerable attention among scholars, pointing to novel forms of investigative reporting as well as new daily practices of news production. This study contributes to existing scholarship by conceptualizing data journalism through distinctions between hard and soft news in relation to service journalism. We analyze news produced by specialized data desks in Swedish public service organizations over a 5-year period (2015–2019) and propose a model for how service journalism attributes can be used as a bridge between the binary categories of hard and soft in data journalism. With this model, we point to how data journalism in public service organizations challenges established notions of soft and hard news and how hybrid production practices open up new research trajectories concerning the societal significance of news in the digital age.
Highlights
Over the past decade, data journalism has become widely established in legacy media organizations, blending traditional practices of news production with statistical analysis, computer science, visualization techniques, and web design, forming a specialized subdomain of journalism characterized by “hybridization” (Bradshaw, 2014)
Like environmental issues, could be seen as hard due to the salience of this theme in global debates, but following Karidi (2018), we categorized environmental issues as soft to facilitate comparisons with findings in international news media research. Bearing this complexity in mind, it is clear that hard news topics do dominate the data journalism content of service radio (SR) as well as service radio (SR) and television (SVT)
While much data journalism scholarship has focused on the democratic promises and professional potentials of data journalism, often as a specialized domain of investigative reporting, the aim of this study has been to broaden the scholarly outlook and assess data journalism content in light of various distinctions between hard and soft news and service journalism
Summary
Data journalism has become widely established in legacy media organizations, blending traditional practices of news production with statistical analysis, computer science, visualization techniques, and web design, forming a specialized subdomain of journalism characterized by “hybridization” (Bradshaw, 2014). Data journalists combine values from open-source culture with traditional journalistic values, as they have aspirations of both being facilitators (enabling others to take action) and gatekeepers (being impactful and steer debates) (Baack, 2018). Many of these studies have foregrounded a positive or at least hopeful view of data journalism based on its ability to illuminate wrongdoing and provide a deeper and more nuanced picture of complex realities. Some scholars implicitly position data journalism within a hard rather than soft framework, pointing, for example, to a dominance of political topics (Loosen et al, 2017; Stalph, 2018). To date, there are no studies that explicitly analyze data journalism in relation to hard and soft news beyond the topic dimension
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