—Review in the Journal of American Statistical Association, Guoqiang Yu, Virginia Tech"Most social scientists would agree that ‘big data’ – the term we use to encapsulate the huge amount of electronic information we generate in our everyday lives – provide the potential for path-breaking research not just into our economic, social, and political lives but also the physical environment we create and inhabit. However, few have the knowledge, or critically, the tools that equip them to realize this potential. This book provides a bridge between computer science, statistics, and the social sciences, demonstrating this new field of ‘data science’ via practical applications. The book is remarkable in many ways. It originates from classes taught by leading practitioners in this area to federal agency research staff, drawing in particular upon the example of a hugely successful project that linked federal research spending to outcomes in terms of patents, job creation, and the subsequent career development of researchers. By making these workbooks accessible, the book takes the novice on a step-by-step journey through complex areas such as database dynamics, data linkage, text analysis, networks and data visualization. The book is a treasure trove of information. It leads the field in the important task of bringing together computer science, statistics, and social science. I strongly recommend that all social scientists with an interest in ‘big data’ immerse themselves in this book."

—Professor Peter Elias CBE, University of Warwick


"The explosive growth in big data and in new technologies to analyze these data is transforming the practice of research in a variety of fields. Foster, et al. provides a well-timed, valuable guide to the new methods and tools associated with big data that can be used to address critical research questions in the social science field. The breadth of the material is impressive, providing a comprehensive summary of the methods and tools as well as practical guidance for their use. A key feature of the guide is the use of a case study to illustrate how big data techniques can be used to address a research question from beginning to end of the project, including providing examples of computer code targeted to specific steps in the project. Any researcher will find this unique guide to be useful, and it is essential reading for any social science practitioner that wants to use the best available data to conduct influential research in the near future."

—Paul Decker, President and CEO, Mathematica Policy Research


"The typical statistics pedagogy has changed. In the past, textbooks assumed that data was hard to obtain, but neatly organized in a single file. Today, data is very easy to obtain from a number of data sources, often very messy, and analysts are now responsible for organizing it in addition to deriving useful insights. Foster, Ghani, Jarmin, Kreuter, and Lane have assembled a book that gives a pointed overview of tools to facilitate the entire digital lifespan of data in this era of analytics. Big Data and Social Science gives an evenhanded look at the myriad of ways to obtain data--whether scraping the web, web APIs, or databases--to conducting statistical analysis to doing analysis when your data cannot fit on a single computer. Meanwhile, they provide sound, diligent advice on pitfalls that still, and will always, exist. A book like this is useful for social scientists, experienced statisticians, econometricians, and computer programmers who want to see the tools available to them. It will also be a helpful text for a budding data scientist who wants a fairly technical preview of the landscape."

—Tom Schenk Jr., Chief Data Officer, City of Chicago


"In Big Data and Social Science, the authors have deftly crafted one of the very best "how-to" books on big data that researchers, enterprise analysts, and government practitioners will find equally valuable. From Nodes, to Edges, to Arcs, the book takes the reader along a near-perfect path to understanding the fundamental elements of constructing a practical and realistic model for Big Data Analysis that any organization can execute by simply following the path outlined in this book. Elegant in its simplicity, Big Data and Social Science is one of those books that every research group and data-analysis team will want to have on their reference shelf."

—Tom Herzog, Former Deputy Commissioner, NY State Department of Corrections and Community Supervision