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

• Main Authors: QIU, Lin, CHAN, Sarah Hian May, CHAN, David
• Format: text
• Language: English
• Published: Institutional Knowledge at Singapore Management University 2017
• Subjects: Big data; Computational social science; Psychology; Social science; Social media; Methodology; Social Psychology and Interaction
• Online Access: https://ink.library.smu.edu.sg/soss_research/2464; https://ink.library.smu.edu.sg/context/soss_research/article/3721/viewcontent/big_data_in_social.pdf
• Institution: Singapore Management University

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.