Big data research guided by sociological theory: a triadic dialogue among big data analysis, theory, and predictive models

A publication (2019 | journal article) of the University of Göttingen

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​Big data research guided by sociological theory: a triadic dialogue among big data analysis, theory, and predictive models​
Luo, J.-D.; Liu, J.; Yang, K. & Fu, X. ​ (2019) 
The Journal of Chinese Sociology6(1) art. 11​.​

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Authors
Luo, Jar-Der
Liu, Jifan
Yang, Kunhao
Fu, Xiaoming 
Abstract
Abstract Computational social science has integrated social science theories and methodology with big data analysis. It has opened a number of new topics for big data analysis and enabled qualitative and quantitative sociological research to provide the ground truth for testing the results of data mining. At the same time, threads of evidence obtained by data mining can inform the development of theory and thereby guide the construction of predictive models to infer and explain more phenomena. Using the example of the Internet data of China’s venture capital industry, this paper shows the triadic dialogue among data mining, sociological theory, and predictive models and forms a methodology of big data analysis guided by sociological theories.
Issue Date
2019
Publisher
Springer
Journal
The Journal of Chinese Sociology 
Organization
Fakultät für Mathematik und Informatik
Language
English

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