Adapting computational text analysis to social science (and vice versa)

Adapting computational text analysis to social science (and vice versa)
复制标题

DOI:
10.1177/2053951715602908
复制
发表时间:
2015-07-01
期刊:
影响因子:
8.5
通讯作者:
DiMaggio, Paul
DiMaggio, Paul
中科院分区:
法学1区
文献类型:
--
作者:
DiMaggio, Paul

文献摘要

被引文献

相似文献

Social scientists and computer scientist are divided by small differences in perspective and not by any significant disciplinary divide. In the field of text analysis, several such differences are noted: social scientists often use unsupervised models to explore corpora, whereas many computer scientists employ supervised models to train data; social scientists hold to more conventional causal notions than do most computer scientists, and often favor intense exploitation of existing algorithms, whereas computer scientists focus more on developing new models; and computer scientists tend to trust human judgment more than social scientists do. These differences have implications that potentially can improve the practice of social science.