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

Author

Lin QIU
Sarah Hian May CHAN
David CHAN, Singapore Management UniversityFollow

Publication Type

Journal Article

Version

publishedVersion

Publication Date

12-2017

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.

Keywords

Big data, Computational social science, Psychology, Social science, Social media, Methodology

Discipline

Psychology | Social Psychology and Interaction

Research Areas

Psychology

Publication

Journal of Computational Social Science

Volume

1

Issue

1

First Page

59

Last Page

66

ISSN

2432-2717

Identifier

10.1007/s42001-017-0013-6

Citation

QIU, Lin, CHAN, Sarah Hian May, & CHAN, David.(2017). Big data in social and psychological science: Theoretical and methodological issues. Journal of Computational Social Science, 1(1), 59-66.

Available at: https://ink.library.smu.edu.sg/soss_research/2464

Copyright Owner and License

Authors

Creative Commons License

This work is licensed under a Creative Commons Attribution-NonCommercial-No Derivative Works 4.0 International License.

Additional URL

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