Big data research guided by sociological theory

A triadic dialogue among big data analysis, theory, and predictive models

Bibliographic Data

ID13059522
AuthorsJar-Der Luo (0000-0002-1387-9849, Tsinghua University, corresponding author), Jifan Liu (Tsinghua University), Kunhao Yang (0000-0002-7654-9441, Tsinghua University), Xiaoming Fu (0000-0002-8012-4753, University of Göttingen)
Year2019
Volume6
Issue1
Publication date2019-07-05
Peer ReviewedYes
Open AccessYes
TypeARTICLE
VenueThe Journal of Chinese Sociology (JOURNAL)
Journal identifiersISSN: 2198-2635 • E-ISSN: 2198-2635
PublisherSpringer Nature (PUBLISHER • SG)
DOI10.1186/s40711-019-0102-4
OpenAlexW2955050622
LanguageEN
Citations received4
References cited27

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

Big data · Computational sociology · Data mining · Data science · Epistemology · Social science · Sociological theory · Sociology · The Internet · World Wide Web · Computer Science · Qualitative Comparative Analysis Research

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