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

Halford, Susan and Savage, Mike (2017) Speaking sociologically with big data: symphonic social science and the future for big data research Sociology, pp. 1-18.

Record type: Article

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.

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More information

Accepted/In Press date: 11 January 2017
Organisations: Social Sciences

Identifiers

Local EPrints ID: 404777
URI: http://eprints.soton.ac.uk/id/eprint/404777
ISSN: 0038-0385
PURE UUID: a88ce75c-94f4-45a5-b690-dfc134eedb5b

Catalogue record

Date deposited: 23 Jan 2017 14:07
Last modified: 18 Jul 2017 04:07

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Contributors

Author: Susan Halford
Author: Mike Savage

University divisions

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