Early social science research about Big Data

Jan Youtie, Alan L. Porter and Ying Huang

Science and Public Policy, 2017, vol. 44, issue 1, 65-74

Abstract: Recent emerging technology policies seek to diminish negative impacts while equitably and responsibly accruing and distributing benefits. Social scientists play a role in these policies, but relatively little quantitative research has been undertaken to study how social scientists inform the assessment of emerging technologies. This paper addresses this gap by examining social science research on ‘Big Data’, an emerging technology of wide interest. This paper analyzes a dataset of fields extracted from 488 social science and humanities papers written about Big Data. Our focus is on understanding the multi-dimensional nature of societal assessment by examining the references upon which these papers draw. We find that eight sub-literatures are important in framing social science research about Big Data. These results indicate that the field is evolving from general sociological considerations toward applications issues and privacy concerns. Implications for science policy and technology assessment of societal implications are discussed.

Keywords: Big Data; bibliometrics; cited references; social science (search for similar items in EconPapers)
Date: 2017
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Persistent link: https://EconPapers.repec.org/RePEc:oup:scippl:v:44:y:2017:i:1:p:65-74.

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