Big data in social and psychological science: theoretical and methodological issues
Big data in social and psychological science: theoretical and methodological issues
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DOI：
10.1007/s42001-017-0013-6
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发表时间：
2018-01-01
影响因子：
3.2
通讯作者：
Chan, David
中科院分区：
文献类型：
--
作者：
Qiu, Lin;Chan, Sarah Hian May;Chan, David
大数据为大规模了解人类行为提供了前所未有的机会。它越来越多地用于社会和心理研究，以揭示个体差异和群体动力学。大数据研究中存在一些理论和方法上的挑战，需要引起注意。在本文中，我们强调了四个问题，即数据驱动与理论驱动的方法，测量有效性，多层次的纵向分析，和数据整合。它们代表了社会科学家在使用大数据时经常面临的常见问题。我们提出这些问题的例子，并提出可能的解决方案。
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.