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

Research output: Contribution to journalArticle

Original languageEnglish
Pages (from-to)1132-1148
Number of pages17
JournalSociology
Volume51
Issue number6
Early online date2 Jun 2017
DOIs
DateAccepted/In press - 11 Jan 2017
DateE-pub ahead of print - 2 Jun 2017
DatePublished (current) - Jun 2017

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.

    Structured keywords

  • Digital Futures

    Research areas

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

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  • Full-text PDF (accepted author manuscript)

    Rights statement: This is the author accepted manuscript (AAM). The final published version (version of record) is available online via Sage at https://journals.sagepub.com/doi/full/10.1177/0038038517698639. Please refer to any applicable terms of use of the publisher.

    Accepted author manuscript, 348 KB, PDF-document

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