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Big Data and Journalism: Epistemology, expertise, economics, and ethics

Journal article
Authors Seth Lewis
Oscar Westlund
Published in Digital Journalism
Volume 3
Issue 3
Pages 447-466
ISSN 2167-0811
Publication year 2015
Published at Department of Journalism, Media and Communication (JMG)
Pages 447-466
Language en
Keywords algorithms, big data, computational journalism, epistemology, expertise, media economics, media innovation, journalism ethics, technology
Subject categories Business Administration, Sociology, Media and Communications, Media Studies, Communication Studies, Human Aspects of ICT, Information Systems, Social aspects, Other Social Sciences


Big data is a social, cultural, and technological phenomenon—a complex amalgamation of digital data abundance, emerging analytic techniques, mythology about data-driven insights, and growing critique about the overall consequences of big-data practices for democracy and society. While media and communication scholars have begun to examine and theorize about big data in the context of media and public life broadly, what are the particular implications for journalism? This article introduces and applies four conceptual lenses—epistemology, expertise, economics, and ethics—to explore both contemporary and potential applications of big data for the professional logic and industrial production of journalism. These distinct yet inter-related conceptual approaches reveal how journalists and news media organizations are seeking to make sense of, act upon, and derive value from big data during a time of exploration in algorithms, computation, and quantification. In all, the developments of big data potentially have great meaning for journalism’s ways of knowing (epistemology) and doing (expertise), as well as its negotiation of value (economics) and values (ethics). Ultimately, this article outlines future directions for journalism studies research in the context of big data.

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