Defining and Mapping Data Journalism and Computational Journalism

A review of typologies and themes

Authored by: Mark Coddington

The Routledge Handbook of Developments in Digital Journalism Studies

Print publication date:  August  2018
Online publication date:  September  2018

Print ISBN: 9781138283053
eBook ISBN: 9781315270449
Adobe ISBN:

10.4324/9781315270449-18

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Abstract

In every era, there is a subset of journalistic practice that draws substantial attention (perhaps inordinately so) from journalists and especially scholars of journalism, outpacing the prevalence of the practice itself or its interest among the public. During the 1990s, the discussion of public journalism ran throughout both journalism scholarship and the news industry itself, while its practice was largely limited to a few well-publicized examples. In the 2000s, citizen journalism became an industry buzzword and the subject of much scholarly rumination, though successful instances of citizen-led news operations and projects were difficult to come by. During this decade, data journalism and its many related forms has become an object of scholarly fixation and much excitement in the industry and in journalism education. Numerous news organizations developed specialized data teams, global data journalism awards were instituted, and attendance at the annual conference of the seminal U.S. group National Institute for Computer-Assisted Reporting (NICAR) tripled between 2010 and 2014 (Stiles, 2017). In academia, universities around the world developed data journalism courses to meet the industry’s demand for those skills (Griffin and Dunwoody, 2016; Hewett, 2016), and scholarship on data journalism boomed.

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