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.
Highlights
Big data analysis1 has drawn great attention to computational social science
This paper focuses in particular on computational sociology
Earlier big data analysis focuses only on the practical and treats collected data as the population. These works do not emphasize random sampling or causal inference but mainly focus on descriptive statistics and correlation analysis. This kind of big data analysis that centers on data mining (Mayer-Schönberger and Cukier, 2014) usually only answers the “what” questions, but not the “how” or the “why” questions
Summary
Big data analysis has drawn great attention to computational social science. This paper focuses in particular on computational sociology. Earlier big data analysis focuses only on the practical and treats collected data as the population These works do not emphasize random sampling or causal inference but mainly focus on descriptive statistics and correlation analysis. This kind of big data analysis that centers on data mining (Mayer-Schönberger and Cukier, 2014) usually only answers the “what” questions, but not the “how” (the mechanism of the process’s unfolding) or the “why” (causal relations) questions. Without answers to these queries, predictive models derived from relevant research lack the capability to make causal inferences (Rubin 1974). When does a currently valid prediction lose its validity? Will a prediction that is valid in the USA be valid in China as well? Can we make inferences about other products using such purchasing behaviors?
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