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Provides an introduction of the data industry to the field of economics This book bridges the gap between economics and data science to help data scientists understand the economics of big data, and enable economists to analyze the data industry. It begins by explaining data resources and introduces the data asset. This book defines a data industry chain, enumerates data enterprises’ business models versus operating models, and proposes a mode of industrial development for the data industry. The author describes five types of enterprise agglomerations, and multiple industrial cluster effects. A discussion on the establishment and development of data industry related laws and regulations is provided. In addition, this book discusses several scenarios on how to convert data driving forces into productivity that can then serve society. This book is designed to serve as a reference and training guide for ata scientists, data-oriented managers and executives, entrepreneurs, scholars, and government employees. Defines and develops the concept of a “Data Industry,” and explains the economics of data to data scientists and statisticians Includes numerous case studies and examples from a variety of industries and disciplines Serves as a useful guide for practitioners and entrepreneurs in the business of data technology The Data Industry: The Business and Economics of Information and Big Data is a resource for practitioners in the data science industry, government, and students in economics, business, and statistics. CHUNLEI TANG, Ph.D., is a research fellow at Harvard University. She is the co-founder of Fudan’s Institute for Data Industry and proposed the concept of the “data industry”. She received a Ph.D. in Computer and Software Theory in 2012 and a Master of Software Engineering in 2006 from Fudan University, Shanghai, China.
Based on an extensive corpus-based study, this revealing book explores how epistemic stance is expressed in the early modern period, and in doing so, presents new methodologies for using corpora to investigate issues in historical pragmatics. It provides a new, corpus-driven method for the analysis of pragmatic functions that rely on context-dependent interpretations. By retrieving passages that include a high-density of the pragmatic function under investigation, the subsequent analysis can reveal previously neglected forms and context-dependent factors. It includes four empirical studies that apply the method to the analysis of epistemic stance in four Early Modern English corpora, the result of which emphasise the importance of context for the expression of stance. It also includes an appendix with inventories of Early Modern English stance expressions, offering starting points for further research studies. It is essential reading for researchers and students in historical pragmatics and corpus pragmatics.