Speaking sociologically with big data: symphonic social science and the future for big data research

Susan Halford, Mike Savage

Research output: Contribution to journalArticle (Academic Journal)peer-review

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Abstract

Recent years have seen persistent tension between proponents of big data analytics, using new forms of digital data to make computational and statistical claims about ‘the social’, and many sociologists sceptical about the value of big data, its associated methods and claims to knowledge. We seek to move beyond this, taking inspiration from a mode of argumentation pursued by Putnam (2000), Wilkinson and Pickett (2009) and Piketty (2014) that we label ‘symphonic social science’. This bears both striking similarities and significant differences to the big data paradigm and – as such – offers the potential to do big data analytics differently. This offers value to those already working with big data – for whom the difficulties of making useful and sustainable claims about the social are increasingly apparent – and to sociologists, offering a mode of practice that might shape big data analytics for the future.
Original languageEnglish
Pages (from-to)1132-1148
Number of pages17
JournalSociology
Volume51
Issue number6
Early online date2 Jun 2017
DOIs
Publication statusPublished - 1 Dec 2017

Structured keywords

  • Digital Societies

Keywords

  • big data
  • computational methods
  • sociology
  • symphonic social science
  • visualisation

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