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

Jar Der Luo*, Jifan Liu, Kunhao Yang, Xiaoming Fu

*この研究の対応する著者

研究成果: Article査読

3 被引用数 (Scopus)

抄録

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.

本文言語English
論文番号11
ジャーナルJournal of Chinese Sociology
6
1
DOI
出版ステータスPublished - 2019 12月 1
外部発表はい

ASJC Scopus subject areas

  • 社会科学(全般)

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