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Small big data: using multiple data-sets to explore unfolding social and economic change

Small big data: using multiple data-sets to explore unfolding social and economic change
Small big data: using multiple data-sets to explore unfolding social and economic change
Bold approaches to data collection and large-scale quantitative advances have long been a preoccupation for social science researchers. In this commentary we further debate over the use of large-scale survey data and official statistics with ‘big data’ methodologists, and emphasise the ability of these resources to incorporate the essential social and cultural heredity that is intrinsic to the human sciences. In doing so, we introduce a series of new data-sets that integrate approximately thirty years of survey data on victimisation, fear of crime and disorder and social attitudes with indicators of socio-economic conditions and policy outcomes in Britain. The data-sets that we outline below do not conform to typical conceptions of ‘big data’. But, we would contend, they are ‘big’ in terms of the volume, variety and complexity of data which has been collated (and to which additional data can be linked) and ‘big’ also in that they allow us to explore key questions pertaining to how social and economic policy change at the national level alters the attitudes and experiences of citizens. Importantly, they are also ‘small’ in the sense that the task of rendering the data usable, linking it and decoding it, required both manual processing and tacit knowledge of the context of the data and intentions of its creators.
2053-9517
Gray, Emily
04ff194d-9985-4638-b702-751948aa5f25
Jennings, Will
2ab3f11c-eb7f-44c6-9ef2-3180c1a954f7
Farrall, Stephen
c0bf4481-60fd-46f3-bc13-114bf4e58dd3
Hay, Colin
1dc2c1eb-c9bc-4f6a-ad7a-aa0038689217
Gray, Emily
04ff194d-9985-4638-b702-751948aa5f25
Jennings, Will
2ab3f11c-eb7f-44c6-9ef2-3180c1a954f7
Farrall, Stephen
c0bf4481-60fd-46f3-bc13-114bf4e58dd3
Hay, Colin
1dc2c1eb-c9bc-4f6a-ad7a-aa0038689217

Gray, Emily, Jennings, Will, Farrall, Stephen and Hay, Colin (2015) Small big data: using multiple data-sets to explore unfolding social and economic change. Big Data & Society. (doi:10.1177/2053951715589418).

Record type: Article

Abstract

Bold approaches to data collection and large-scale quantitative advances have long been a preoccupation for social science researchers. In this commentary we further debate over the use of large-scale survey data and official statistics with ‘big data’ methodologists, and emphasise the ability of these resources to incorporate the essential social and cultural heredity that is intrinsic to the human sciences. In doing so, we introduce a series of new data-sets that integrate approximately thirty years of survey data on victimisation, fear of crime and disorder and social attitudes with indicators of socio-economic conditions and policy outcomes in Britain. The data-sets that we outline below do not conform to typical conceptions of ‘big data’. But, we would contend, they are ‘big’ in terms of the volume, variety and complexity of data which has been collated (and to which additional data can be linked) and ‘big’ also in that they allow us to explore key questions pertaining to how social and economic policy change at the national level alters the attitudes and experiences of citizens. Importantly, they are also ‘small’ in the sense that the task of rendering the data usable, linking it and decoding it, required both manual processing and tacit knowledge of the context of the data and intentions of its creators.

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More information

Accepted/In Press date: 11 May 2015
Published date: 25 June 2015
Organisations: Politics & International Relations

Identifiers

Local EPrints ID: 376969
URI: http://eprints.soton.ac.uk/id/eprint/376969
ISSN: 2053-9517
PURE UUID: 2b0315ab-4b51-488d-9d9d-3ca176f1fb6c
ORCID for Will Jennings: ORCID iD orcid.org/0000-0001-9007-8896

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Date deposited: 18 May 2015 10:47
Last modified: 23 Jul 2022 02:04

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Contributors

Author: Emily Gray
Author: Will Jennings ORCID iD
Author: Stephen Farrall
Author: Colin Hay

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