Yunsong Chen – författare

Chen, He and Yan present a range of applications of multiple-source big data to core areas of contemporary sociology, demonstrating how a theory-guided approach to macrosociology can help to understand social change in China, especially where traditional approaches are limited by constrained and biased data.

In each chapter of the book, the authors highlight an application of theory-guided macrosociology that has the potential to reinvigorate an ambitious, open-minded and bold approach to sociological research. These include social stratification, social networks, medical care, and online behaviours among many others. This research approach focuses on macro-level social process and phenomena by using quantitative models to statistically test for associations and causalities suggested by a clearly hypothesised social theory. By deploying theory-oriented macrosociology where it can best assure macro-level robustness and reliability, big data applications can be more relevant to and guided by social theory.

An essential read for sociologists with an interest in quantitative and macro-scale research methods, which also provides fascinating insights into Chinese society as a demonstration of the utility of its methodology.

Chen, He and Yan present a range of applications of multiple-source big data to core areas of contemporary sociology, demonstrating how a theory-guided approach to macrosociology can help to understand social change in China, especially where traditional approaches are limited by constrained and biased data.

In each chapter of the book, the authors highlight an application of theory-guided macrosociology that has the potential to reinvigorate an ambitious, open-minded and bold approach to sociological research. These include social stratification, social networks, medical care, and online behaviours among many others. This research approach focuses on macro-level social process and phenomena by using quantitative models to statistically test for associations and causalities suggested by a clearly hypothesised social theory. By deploying theory-oriented macrosociology where it can best assure macro-level robustness and reliability, big data applications can be more relevant to and guided by social theory.

An essential read for sociologists with an interest in quantitative and macro-scale research methods, which also provides fascinating insights into Chinese society as a demonstration of the utility of its methodology.

This book presents a series of studies focusing on the role of social capital in the labor market and beyond. Using the effect of individual social capital on labor markets as an example, this book pays special attention to the origins of and solutions to the endogeneity problem. It uses several identification strategies to systematically test for the causal effects of social capital.

First, this book constitutes the first attempt to offer a systematic account of the progress made by social scientists in improving causal inferences into the role of social capital in labor markets. Second, the book adopts specialized approaches—both classical and new—toward different sources of endogeneity. Incorporating the latest research from outside fields, such as economics, into sociological research is a small but significant methodological innovation. Third, in addition to empirical research, this book undertakes an innovative exploration of the theory of social capital. It creativelyexplains the dynamic evolution of social capital, which helps balance objectivism and subjectivism when analyzing interpersonal actions.

For sociologists who focus on quantitative research methods and social capital, scholars who study Chinese societies, and related students, this book provides both advanced methods and rich empirical research.