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

Springer Science and Business Media LLC - 2019
Jar-Der Luo1, Jifan Liu2, Kunhao Yang2, Xiaoming Fu3
1Sociology Department Social Science School, and Public Administration School, Tsinghua University, Beijing, People’s Republic of China
2Sociology Department, Tsinghua University, Beijing, People’s Republic of China
3School of Mathematics and Computer Science, University of Göttingen, Göttingen, Germany

Tóm tắt

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.

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