Data-Driven-Journalism Literature Explorer

The DDJ Literature Explorer helps you to explore existing research literature on data journalism. It was developed in the course of the paper "The datafication of data journalism scholarship: Focal points, methods, and research propositions for the investigation of data-intensive newswork". Over the past years this emerging journalistic practice has been established and has also attracted significant attention from journalism scholars. It was time to take a closer look at the existing research literature in order to find out more about how this literature has been developing. Where are the research gaps and what does the future of data journalism research hold? These questions were tackled by carefully selecting a corpus of scholarly literature with empirical foundation in data journalism. This corpus was analyzed with a mixed method approach using qualitative and quantitative techniques. In this way the development of the literature over time could be illustrated and the most influential publications could be identified. Also, often-used theoretical frameworks and the applied research designs hinted at certain tendencies and gaps in the research literature on data journalism, for example, the dominance of qualitative research design over quantitative ones. Also a shortcoming of cross-national investigations and ethnographic studies was visible.

Publication

The datafication of data journalism scholarship: Focal points, methods, and research propositions for the investigation of data-intensive newswork. Journalism, 2017
Julian Ausserhofer, Robert Gutounig, Michael Oppermann, Sarah Matiasek, and Eva Goldgruber