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Does ‘bigger’ mean ‘better’? Pitfalls and shortcuts associated with big data for social research

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  • Paolo Giardullo

Abstract

‘Big data is here to stay.’ This key statement has a double value: is an assumption as well as the reason why a theoretical reflection is needed. Furthermore, Big data is something that is gaining visibility and success in social sciences even, overcoming the division between humanities and computer sciences. In this contribution some considerations on the presence and the certain persistence of Big data as a socio-technical assemblage will be outlined. Therefore, the intriguing opportunities for social research linked to such interaction between practices and technological development will be developed. However, despite a promissory rhetoric, fostered by several scholars since the birth of Big data as a labelled concept, some risks are just around the corner. The claims for the methodological power of bigger and bigger datasets, as well as increasing speed in analysis and data collection, are creating a real hype in social research. Peculiar attention is needed in order to avoid some pitfalls. These risks will be analysed for what concerns the validity of the research results ‘obtained through Big data. After a pars distruens, this contribution will conclude with a pars construens; assuming the previous critiques, a mixed methods research design approach will be described as a general proposal with the objective of stimulating a debate on the integration of Big data in complex research projecting. Copyright Springer Science+Business Media Dordrecht 2016

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  • Paolo Giardullo, 2016. "Does ‘bigger’ mean ‘better’? Pitfalls and shortcuts associated with big data for social research," Quality & Quantity: International Journal of Methodology, Springer, vol. 50(2), pages 529-547, March.
    • Handle: RePEc:spr:qualqt:v:50:y:2016:i:2:p:529-547
    DOI: 10.1007/s11135-015-0162-8
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    References listed on IDEAS

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    1. Lieberman, Evan S., 2005. "Nested Analysis as a Mixed-Method Strategy for Comparative Research," American Political Science Review, Cambridge University Press, vol. 99(3), pages 435-452, August.
    2. Rajagopal, 2014. "The Human Factors," Palgrave Macmillan Books, in: Architecting Enterprise, chapter 9, pages 225-249, Palgrave Macmillan.
    3. Jeremy Ginsberg & Matthew H. Mohebbi & Rajan S. Patel & Lynnette Brammer & Mark S. Smolinski & Larry Brilliant, 2009. "Detecting influenza epidemics using search engine query data," Nature, Nature, vol. 457(7232), pages 1012-1014, February.
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