The datafication of data journalism scholarship: Focal points, methods, and research propositions for the investigation of data-intensive newswork

Abstract

This article explores the existing research literature on data journalism. Over the past years, this emerging journalistic practice has attracted significant attention from researchers in different fields and produced an increasing number of publications across a variety of channels. To better understand its current state, we surveyed the published academic literature between 1996 and 2015 and selected a corpus of 40 scholarly works that studied data journalism and related practices empirically. Analyzing this corpus with both quantitative and qualitative techniques allowed us to clarify the development of the literature, influential publications, and possible gaps in the research caused by the recurring use of particular theoretical frameworks and research designs. This article closes with proposals for future research in the field of data-intensive newswork.

Contributions of academic articles to the practice of journalism and data management

“…The SLR is frequently applied to develop insights and future research paths or review methodologies applied (Moher et al, 2009;López-Cantos, 2015;Massaro, Dumay, and Guthrie, 2016;Ausserhofer et al, 2017).…”

“…The final purpose of this article is to know what can be learnt about skills related to the use of data in journalism from the contributions of researches published in academic journals. There have been previous literature reviews for identifying influential publications and gaps in the research of data journalism (Ausserhofer et al, 2017), for identifying methodologies (López-Cantos, 2015) or opportunities for innovation in computational journalism (Diakopoulos, 2012). However, this paper differs from these previous contributions in the method used for the selection of the contributions and the research questions made.…”

Algorithms, Automation, and News

“…That question animates this special issue of Digital Journalism. We began working on this project more than two years ago under the premise that, although the journalism studies literature had made great strides in assessing the digitization of news in the 2000s and the emergence, in the 2010s, of data, code, and software as key organizing components of contemporary journalism (see, e.g., Anderson, 2013;Ausserhofer et al 2017; Lewis and Westlund 2015a; Usher 2016; Weber and Kosterich 2018), there was yet an opportunity to more fully capture and conceptualize the particular influence of algorithms and automation in newswork. By the mid-2010s, it had become clear that fully automated and semi-automated forms of gathering, filtering, composing, and sharing news had assumed a greater place in a growing number of newsrooms (Diakopoulos 2019;D€ orr 2016), opening the possibility that there were places where shifts in the norms, patterns, and routines of news production were happening and even that, at a more fundamental level, taken-forgranted ideas about who (or what) does journalism were being challenged (Lewis, Guzman, and Schmidt 2019;Primo and Zago 2015).…”

Hybrids, materiality, and black boxes: Concepts of actor‐network theory in data journalism research

“…A structured review of 40 studies on data journalism research by Ausserhofer, Gutounig, Oppermann, Matiasek, and Goldgruber () identifies Parasie and Dagiral's () study on data‐driven journalism in Chicago that explicitly draws on ANT, as one of the most cited works in this research area. The authors found that “programmer‐journalists” (p. 860) propose epistemologies that are deeply linked to computer skills and technical artefacts.…”