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Big data in social and psychological science: theoretical and methodological issues

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Abstract

Big data presents unprecedented opportunities to understand human behavior on a large scale. It has been increasingly used in social and psychological research to reveal individual differences and group dynamics. There are a few theoretical and methodological challenges in big data research that require attention. In this paper, we highlight four issues, namely data-driven versus theory-driven approaches, measurement validity, multi-level longitudinal analysis, and data integration. They represent common problems that social scientists often face in using big data. We present examples of these problems and propose possible solutions.

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Authors and Affiliations

  1. School of Social Sciences, Nanyang Technological University, Singapore, Singapore

    Lin Qiu & Sarah Hian May Chan

  2. Behavioural Sciences Institute, Singapore Management University, Singapore, Singapore

    David Chan

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  1. Lin Qiu
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  2. Sarah Hian May Chan
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  3. David Chan
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Correspondence to Lin Qiu.

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Qiu, L., Chan, S.H.M. & Chan, D. Big data in social and psychological science: theoretical and methodological issues. J Comput Soc Sc 1, 59–66 (2018). https://doi.org/10.1007/s42001-017-0013-6

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  • DOI: https://doi.org/10.1007/s42001-017-0013-6

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