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

Seth C. Lewis, Oscar Westlund

Research output: Contribution to journalArticlepeer-review

98 Scopus citations


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.

Original languageEnglish (US)
Pages (from-to)447-466
Number of pages20
JournalDigital Journalism
Issue number3
StatePublished - May 4 2015


  • algorithms
  • big data
  • computational journalism
  • epistemology
  • expertise
  • journalism ethics
  • media economics
  • media innovation
  • technology

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