Big Data in Psychology: Introduction to the Special Issue

被引:62
|
作者
Harlow, Lisa L. [1 ]
Oswald, Frederick L. [2 ]
机构
[1] Univ Rhode Isl, Dept Psychol, Kingston, RI 02881 USA
[2] Rice Univ, Dept Psychol, Houston, TX 77251 USA
基金
美国国家卫生研究院;
关键词
big data; machine learning; statistical learning theory; social media data; digital footprint;
D O I
10.1037/met0000120
中图分类号
B84 [心理学];
学科分类号
04 ; 0402 ;
摘要
The introduction to this special issue on psychological research involving big data summarizes the highlights of 10 articles that address a number of important and inspiring perspectives, issues, and applications. Four common themes that emerge in the articles with respect to psychological research conducted in the area of big data are mentioned, including: (a) The benefits of collaboration across disciplines, such as those in the social sciences, applied statistics, and computer science. Doing so assists in grounding big data research in sound theory and practice, as well as in affording effective data retrieval and analysis. (b) Availability of large data sets on Facebook, Twitter, and other social media sites that provide a psychological window into the attitudes and behaviors of a broad spectrum of the population. (c) Identifying, addressing, and being sensitive to ethical considerations when analyzing large data sets gained from public or private sources. (d) The unavoidable necessity of validating predictive models in big data by applying a model developed on 1 dataset to a separate set of data or hold-out sample. Translational abstracts that summarize the articles in very clear and understandable terms are included in Appendix A, and a glossary of terms relevant to big data research discussed in the articles is presented in Appendix B.
引用
收藏
页码:447 / 457
页数:11
相关论文
共 50 条