Editorial: Big data and machine learning in sociology

被引：5
作者：
Leitgoeb, Heinz [1 ,2 ]
Prandner, Dimitri [3 ]
Wolbring, Tobias [4 ]
机构：
[1] Univ Leipzig, Inst Sociol, Leipzig, Germany
[2] Goethe Univ Frankfurt, Inst Sociol, Frankfurt, Germany
[3] Univ Linz, Inst Sociol, Linz, Austria
[4] Univ Erlangen Nurnberg, Inst Labour Market & Socioecon, Nurnberg, Germany
来源：
FRONTIERS IN SOCIOLOGY | 2023年 / 8卷
关键词：
big data; machine learning; computational social science; digitalization; artificial intelligence; social science research methodology; SOCIAL-SCIENCE; CAUSAL MECHANISMS; PROBABILITY; INFERENCE;
D O I：
10.3389/fsoc.2023.1173155
中图分类号：
C91 [社会学];
学科分类号：
030301 ; 1204 ;
摘要：
引用
收藏
页数：7
相关论文
共 84 条
[1]   Wikipedia, sociology, and the promise and pitfalls of Big Data [J].
Adams, Julia ;
Brueckner, Hannah .
BIG DATA & SOCIETY, 2015, 2 (02)
[2]   Comparing Social Science and Computer Science Workflow Processes for Studying Group Interactions [J].
Allen, Joseph A. ;
Fisher, Colin ;
Chetouani, Mohamed ;
Chiu, Ming Ming ;
Gunes, Hatice ;
Mehu, Marc ;
Hung, Hayley .
SMALL GROUP RESEARCH, 2017, 48 (05) :568-590
[3]   Methods for big data in social sciences [J].
Amaturo, Enrica ;
Aragona, Biagio .
MATHEMATICAL POPULATION STUDIES, 2019, 26 (02) :65-68
[4]   TOTAL ERROR IN A BIG DATA WORLD: ADAPTING THE TSE FRAMEWORK TO BIG DATA [J].
Amaya, Ashley ;
Biemer, Paul P. ;
Kinyon, David .
JOURNAL OF SURVEY STATISTICS AND METHODOLOGY, 2020, 8 (01) :89-119
[5]  
Anderson C., 2008, The end of theory: The data deluge makes the scientific method obsolete. wired
[6]   Machine Learning Methods That Economists Should Know About [J].
Athey, Susan ;
Imbens, Guido W. .
ANNUAL REVIEW OF ECONOMICS, VOL 11, 2019, 2019, 11 :685-725
[7]  
Beyer M.A. Laney., 2012, The Importance of Big Data: A Definition
[8]  
Biemer P. P., 2021, Big Data Meets Survey Science: A Collection of Innovative Methods, P133
[9]  
Bishop C., 2006, Pattern Recognition and Machine Learning
[10]   Science and data science [J].
Blei, David M. ;
Smyth, Padhraic .
PROCEEDINGS OF THE NATIONAL ACADEMY OF SCIENCES OF THE UNITED STATES OF AMERICA, 2017, 114 (33) :8689-8692
123456789