Machine Learning for Social Science: An Agnostic Approach

IF 9.7 1区 社会学 Q1 POLITICAL SCIENCE Annual Review of Political Science Pub Date : 2021-03-05 DOI:10.1146/ANNUREV-POLISCI-053119-015921
Justin Grimmer, Margaret E. Roberts, Brandon M Stewart
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引用次数: 94

Abstract

Social scientists are now in an era of data abundance, and machine learning tools are increasingly used to extract meaning from data sets both massive and small. We explain how the inclusion of mac...
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社会科学的机器学习:不可知论方法
社会科学家现在处于一个数据丰富的时代,机器学习工具越来越多地用于从大量和小型数据集中提取意义。我们解释了mac…
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来源期刊
CiteScore
15.20
自引率
4.60%
发文量
23
期刊介绍: The Annual Review of Political Science has been published since 1998 to provide comprehensive coverage of critical advancements in the field. It encompasses a wide range of subjects within Political Science, such as political theory and philosophy, international relations, political economy, political behavior, American and comparative politics, public administration and policy, and methodology.
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