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AbstractMany scholars have used local Chinese county gazetteers for historical and socioeconomic analyses, yet little research has examined the completeness of coverage or the biases in reporting that characterize the compilation of these gazetteers. In this paper, we provide a novel source for studying Chinese political movements and local history under the communist regime after 1949: the internal-discussion drafts of county gazetteers (xianzhi pingyigao). Our findings constitute the first study to use internal review drafts to examine the authenticity and credibility of county gazetteers. Prior to their publication, gazetteer drafts are compiled by a team of editors and typically receive at least three rounds of rigorous internal review. These internal-discussion drafts are subject to a prolonged and strict process of self and external censorship. Our analysis engages in a close comparison of text samples extracted from two versions of local gazetteers collected from four counties in Guangxi province. Compared to the draft versions, we find evidence of serious data manipulation and a tendency to underreport historical events in the published editions. Our research evidently demonstrates the process of historiography editing and reveals how local history is presented through the lens of government public documents in China.

Applying a novel approach based on online query volume data, this study provides the first large-scale portrait of revolutionary nostalgia among the Chinese, undertaking an empirical analysis of how the aggregate level of nostalgia is shaped. For each Chinese province, we use the normalized frequency of searches for red songs on Baidu, the most widely used online search engine in China, to quantify the local level of nostalgia. We find that the evolving trends of nostalgia among the provinces are similar but stratified. The results from the dynamic panel data analysis using the Generalized Method of Moments indicate that revolutionary nostalgia is significantly affected by a set of socio-economic determinants, including GDP per capita, income inequality, social development, legal development and the degree of globalization. (China Q/GIGA)

AbstractApplying a novel approach based on online query volume data, this study provides the first large-scale portrait of revolutionary nostalgia among the Chinese, undertaking an empirical analysis of how the aggregate level of nostalgia is shaped. For each Chinese province, we use the normalized frequency of searches for red songs on Baidu, the most widely used online search engine in China, to quantify the local level of nostalgia. We find that the evolving trends of nostalgia among the provinces are similar but stratified. The results from the dynamic panel data analysis using the Generalized Method of Moments indicate that revolutionary nostalgia is significantly affected by a set of socio-economic determinants, including GDP per capita, income inequality, social development, legal development and the degree of globalization.

Cover -- Half Title -- Series Page -- Title Page -- Copyright Page -- Table of Contents -- List of figures -- List of tables -- Preface -- Part I Introduction -- Chapter 1 Bringing big data to quantitative macrosociology -- Part II Mapping public discourse and social stratification -- Chapter 2 Social stratification as a public discourse in China, 1949-2008 -- Chapter 3 Public concerns about class immobility and economic inequality -- Chapter 4 Self-perceived social mobility and class solidification -- Chapter 5 Stratified nostalgia for the Chinese revolutions -- Part III Portraying social transformations and cultural practice -- Chapter 6 The international visibility of Chinese cities in modern times -- Chapter 7 The cultural determinant of foreign direct investment -- Chapter 8 The effect of cultural familiarity on inbound tourism -- Chapter 9 Coauthor networks in China's humanities and social sciences -- Part IV Revealing public health and community wellness -- Chapter 10 Evaluating effect of PM2.5 exposure on suicidal ideation -- Chapter 11 Forecasting trends in prevalence and incidence of HIV/AIDS -- Chapter 12 Profiling the vaping epidemic and public favorites on e-cigarettes -- Chapter 13 Measuring public concerns in LGBT issues -- References -- Index.

"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"--