Television by the numbers: The challenges of audience measurement in the age of Big Data

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This article examines recent innovations in how television audiences are measured, paying particular attention to the industry's growing efforts to utilize the large bodies of data generated through social media platforms – a paradigm of research known as Big Data. Although Big Data is considered by many in the television industry as a more veracious model of audience research, this essay uses Boyd and Crawford's (2011) `Six Provocations of Big Data' to problematize and interrogate this prevailing industrial consensus. In doing so, this article explores both the affordances and the limitations of this emerging research paradigm – the latter having largely been ignored by those in the industry – and considers the consequences of these developments for the production culture of television more broadly. Although the full impact of the television industry's adoption of Big Data remains unclear, this article traces some preliminary connections between the introduction of these new measurement practices and the production culture of contemporary television. First, I demonstrate how the design of Big Data privileges real-time analysis, which, in turn, encourages increased investment in ‘live’ and/or ‘event’ television. Second, I argue that despite its potential to produce real-time insights, the scale of Big Data actually limits its utility in the context of the creative industries. Third, building on this discussion of the debatable value and applicability of Big Data, I describe how the introduction of social media metrics is further contributing to a ‘data divide’ in which access to these new information data sets is highly uneven, generally favouring institutions over individuals. Taken together, these three different but overlapping developments provide evidence that the introduction of Big Data is already having a notable effect on the television industry in a number of interesting and unexpected ways.
Original languageEnglish
Pages (from-to)113-132
Number of pages20
Issue number1
Early online date30 Mar 2017
Publication statusPublished - 1 Feb 2019


  • big data
  • television
  • Nielsen
  • BARB
  • Audience
  • real-time
  • audience research
  • Apache

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