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

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

3 Citations (Scopus)

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.

Original languageEnglish
Article number11
JournalJournal of Chinese Sociology
Volume6
Issue number1
DOIs
Publication statusPublished - 2019 Dec 1
Externally publishedYes

Keywords

  • Big data analysis
  • Circle theory
  • Computational social science
  • Dynamic network
  • Embeddedness theory

ASJC Scopus subject areas

  • Social Sciences(all)

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