Trade-Offs, Limitations, and Promises of Big Data in Social Science Research

被引:11
|
作者
White, Patricia [1 ]
Breckenridge, R. Saylor [2 ,3 ,4 ,5 ]
机构
[1] Natl Sci Fdn, Arlington, VA 22230 USA
[2] Natl Sci Fdn, Sociol Program, Arlington, VA 22230 USA
[3] Natl Sci Fdn, Directorate Social Behav & Econ Sci SBE, Div Social & Econ Sci SES, Bldg Community & Capac Data Intens Res Social Beh, Arlington, VA 22230 USA
[4] Natl Sci Fdn, SBE, SES, Methodol Measurement & Stat Program, Arlington, VA 22230 USA
[5] Wake Forest Univ, Dept Sociol, Winston Salem, NC 27109 USA
关键词
big data; scientific method; social science; National Science Foundation (NSF);
D O I
10.1111/ropr.12078
中图分类号
D0 [政治学、政治理论];
学科分类号
0302 ; 030201 ;
摘要
The promise of "big data" is a grand one. The collection and aggregation of massive datasets and the development of analytical tools by which to study these data is part of cutting-edge efforts across scientific disciplines, with social, behavioral, and economic sciences leading the way in many of these efforts. There has been a recent rise in National Science Foundation funding for "big data" research across directorates that coincides with scholarly, public, and governmental attention to the topic. Nonetheless, there are limitations and trade-offs to "big data" research, particularly as it corresponds to scientific modes of inquiry and the limited range of topics that fall under its umbrella, that must be recognized and incorporated into the general understanding of its long-term promise.
引用
收藏
页码:331 / 338
页数:8
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