Big Data and Social Science
Data Science Methods and Tools for Research and Practice
Preface to the 2nd edition
The class on which this book is based was created in response to a very real challenge: how to introduce new ideas and methodologies about economic and social measurement into a workplace focused on producing high-quality statistics. Since the first edition of this book came out we have been fortunate to train over 450 participants in the Applied Data Analytics classes, resulting in increased data analytics capacity, both in terms of human and technical resources. What we learned in delivering these classes greatly influenced the 2nd edition. We also added an entire new chapter on Bias and Fairness in Machine Learning, and re-organized the book chapters somewhat.
As with any book, there are many people to be thanked. The Coleridge Initiative team at New York University, the University of Maryland and the University of Chicago were critical in shaping the format and structure - we are particularly grateful to Clayton Hunter, Jody Derezinski Williams, Graham Henke, Jonathan Morgan, Drew Gordon, Avishek Kumar, Brian Kim, Christoph Kern, and all the book chapter authors for their contributions to the second edition.
We also thank the critical reviewers solicited from CRC Press and everyone from whom we got revision suggestions online, in particular Stas Kolenikov, who carefully examined the first edition and suggested updates. We owe a great debt of gratitude to the project editor, Vaishali Singh, and the publisher, Rob Calver, for their hard work and dedication.