IDEAS home Printed from https://ideas.repec.org/a/spr/jcsosc/v1y2018i1d10.1007_s42001-017-0013-6.html
   My bibliography  Save this article

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

Author

Listed:
  • Lin Qiu

    (Nanyang Technological University)

  • Sarah Hian May Chan

    (Nanyang Technological University)

  • David Chan

    (Singapore Management University)

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.

Suggested Citation

  • Lin Qiu & Sarah Hian May Chan & David Chan, 2018. "Big data in social and psychological science: theoretical and methodological issues," Journal of Computational Social Science, Springer, vol. 1(1), pages 59-66, January.
  • Handle: RePEc:spr:jcsosc:v:1:y:2018:i:1:d:10.1007_s42001-017-0013-6
    DOI: 10.1007/s42001-017-0013-6
    as

    Download full text from publisher

    File URL: http://link.springer.com/10.1007/s42001-017-0013-6
    File Function: Abstract
    Download Restriction: Access to the full text of the articles in this series is restricted.

    File URL: https://libkey.io/10.1007/s42001-017-0013-6?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Alex Luscombe & Kevin Dick & Kevin Walby, 2022. "Algorithmic thinking in the public interest: navigating technical, legal, and ethical hurdles to web scraping in the social sciences," Quality & Quantity: International Journal of Methodology, Springer, vol. 56(3), pages 1023-1044, June.
    2. Qianjia Huang & Vivek K. Singh & Pradeep K. Atrey, 2018. "On cyberbullying incidents and underlying online social relationships," Journal of Computational Social Science, Springer, vol. 1(2), pages 241-260, September.
    3. Alnoor Bhimani, 2020. "Digital data and management accounting: why we need to rethink research methods," Journal of Management Control: Zeitschrift für Planung und Unternehmenssteuerung, Springer, vol. 31(1), pages 9-23, April.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:spr:jcsosc:v:1:y:2018:i:1:d:10.1007_s42001-017-0013-6. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    We have no bibliographic references for this item. You can help adding them by using this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.springer.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.