The Datafication of Journalism

Session Submission Type: Panel

Abstract

‘Datafication’ is not just a grand narrative used to describe how digitization is transforming our media environment, in a much more fundamental way it is a story about how numerical data have come to represent and influence social reality. These developments, however, do not follow a linear trajectory nor do they take place at the same speed or in similar ways to developments in different social domains. We are aiming to consider journalism as a field that is destined to be the ideal case study for the expansion of our understanding of datafication. This is because journalism is both deeply concerned with covering the consequences of datafication while at the same time is itself profoundly affected by them. We can observe the development of a new style of reporting based on ever more (publicly) available data sets (data journalism), an escalating implementation of computational processes into all stages of (often new forms of) news production and newsroom routines (computational journalism), varied attempts to make sense of an ever growing amount of audiences’ digital traces (audience measurement) as well as developments that even allow us to speak of the ‘algorithmicization of journalism’ which is not only having a fundamental effect on news work but is literally transforming news media as an institutional field.

This panel brings together research from a variety of perspectives to offer a holistic interpretation of journalism’s increasing datafication. It does so by considering the latest developments in the field from a historical perspective as part of a concerted effort to avoid the misconception that this process is a strictly contemporary phenomenon. To these ends, C.W. Anderson traces the history of data journalism back to the 1960s and ‘70s and distills data journalism as we know it today into five socio-historical events. Turning to the present (and the recent past), Julius Reimer and Wiebke Loosen use standardised content analysis to retrace the developments of data journalism by assessing projects nominated for the Data Journalism Award between 2013 and 2016. Edson C. Tandoc Jr. sheds light on the influence audience metrics are having on journalists’ conceptions of themselves, their audiences and on their professional norms and values based on three surveys in the United States. Finally, Nicholas Diakopoulos takes us a step further by suggesting that news media should be conceptualized as a “human-algorithm system”, forcing us to reconsider journalism at both the level of the author and of the institution and to question the very notions of newsworthiness and accountability.

Sub Unit

• Journalism Studies

Chair

• Wiebke Loosen, Hans-Bredow Institute

Individual Presentations

• Datafication, Institutionalization, or Both: The Many Paths of Data Journalism - C.W. Anderson, University of Leeds

• Mining Data, Refining Journalism? Data Journalism’s Development and Critical Potential - Julius Reimer, Hans-Bredow-Institut für Medienforschung; Wiebke Loosen, Hans-Bredow Institute

• From Letters to Numbers: How Audience Quantification Affects News Construction - Edson Tandoc, Wee Kim Wee School of Communication & Information, Nanyang Technological U

• Automating the Media: The Interplay of Algorithms and People - Nicholas Diakopoulos, Northwestern University