Journalism based on vast amounts of data and numerical information can be divided into three distinct sub-groups, writes PhD. candidate Mark Coddington of University of Texas. According to Coddington, these groups are computer assisted reporting (CAR), data journalism and computational journalism. The typology is meant to support further research over the epistemological foundations of different, modern forms of journalism.
The sub-groups are distinguished by their differing emphasis’ and orientations toward a set of four factors: professional orientation, that can be either professional or networked; openness, that is either opaque or transparent; epistemology, that relies either on big data or sampling; vision of public, that can either be passive or active. For example, where Coddington classifies the professional orientation of CAR as heavily “professional”, it’s strongly “networked” for data journalism.
Mark Coddington’s article “Clarifying journalism’s quantitative turn” has been published online as a preprint of the journal Digital Journalism.