@article{94c9d2000f5043f583e7577e877a272e,
title = "Big data research guided by sociological theory: a triadic dialogue among big data analysis, theory, and predictive models",
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{\textquoteright}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.",
keywords = "Big data analysis, Circle theory, Computational social science, Dynamic network, Embeddedness theory",
author = "Luo, {Jar Der} and Jifan Liu and Kunhao Yang and Xiaoming Fu",
note = "Funding Information: Examples presented in this paper come from multiple other papers that the authors have collaborated with others (Luo et al., 2014 ; Zhou et al., 2016 ; Luo et al., 2018a , b , c ; Gu et al. 2019 ). We hereby thank all these authors. Moreover, the authors thank the student exchange program between the School of Social Science of Tsinghua University and University of G{\"o}ttingen in Germany (IDS – SSP – 2017001), which is supported by the Institution of Data Science of Tsinghua University. This article also received support from Tacent Social Research Center, project “Analyzing Ego-Centered Network by Mining of Wechat and QQ Data,” Project number: 20162001703. Funding Information: The authors thank the student exchange program between the School of Social Science of Tsinghua University and University of G{\"o}ttingen in Germany (IDS–SSP–2017001), which is supported by the Institution of Data Science of Tsinghua University. This article also gets the support of Tacent Co. Tacent Social Research Center, project “Analyzing Ego-Centered Network by Mining of Wechat and QQ Data”, Project number: 20162001703. Publisher Copyright: {\textcopyright} 2019, The Author(s).",
year = "2019",
month = dec,
day = "1",
doi = "10.1186/s40711-019-0102-4",
language = "English",
volume = "6",
journal = "Journal of Chinese Sociology",
issn = "2198-2635",
publisher = "Springer Open",
number = "1",
}