Bit by Bit: Social Research in the Digital Age

(Hardback)

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An innovative and accessible guide to doing social research in the digital age In just the past several years, we have witnessed the birth and rapid spread of social media, mobile phones, and numerous other digital marvels. In addition to changing how we live, these tools enable us to collect and process data about human behavior on a scale never

Reviews

"Winner of the 2019 PROSE Award in Textbook / Social Sciences, Association of American Publishers"
"Winner of the AAPOR Book Award, American Association for Public Opinion Research"
"Salganik is one of the first natural-born computational social scientists, a sociologist whose doctoral work was one of the early landmark projects in the field. Bit by Bit is 90% textbook, 10% biography, putting into personal context issues that Salganik was among the first to wrestle with. . . . The text is clearly written--even breezy, in parts. It puts the reader in the shoes of the researcher: What decisions were made, why, and were those the best choices It is suitable for an advanced undergraduate or graduate class in methodology, with a rigorous, mathematical appendix and a range of useful problems at the conclusion of each chapter."---David Lazer, Science
"This is a book to return to time and again. . . . Bit by Bit should be widely read by those engaging in social research, as well as beyond."---Farida Vis, Times Higher Education
"An enticing and important field guide to the new frontier of digital social research that will be of interest whether one is trying to figure out how to do more evidence-based policymaking or simply sell more toothpaste online. Impeccably organized and beautifully written in clear and accessible prose, the book doubles as a methods textbook for university students studying social and data sciences (or any field where research is at the center)."---Beth Noveck, Forbes
"Given the books breadth, it is a recommended read for all scholars interested in the role that the internet and big data can play in social research."---Tatsiana Amosaya, Canadian Journal of Sociology
"The implications and potential for social science arising from the availability of large amounts of data have been comparatively overlooked. This book provides a welcome insight into what can be achieved, and also an exemplar curriculum for graduate studies."---Thomas King, Journal of the Royal Statistical Society
"A timely and important must-read for anyone interested in the intersection of social science and big data."---Magdalena Wojcieszak, International Journal of Press/Politics
"Salganik offers what is truly a Swiss Army knife for learning and teaching computational social science. The book is equal parts explanation of what computational social science is, lessons on how to do computational social science, and recommendations for how computational social science should grow as an interdisciplinary field."---Marshall A. Taylor, Teaching Sociology
"This is an easy review. Buy this book. No matter your competence in data analysis, your experience in running experiments, or your ability to understand research papers, you will find nuggets of information that will be useful for your development as an economist professional or not."---Ian Bright, Society of Professional Economists

Author Bio

Matthew J. Salganik is professor of sociology at Princeton University, where he is also affiliated with the Center for Information Technology Policy and the Center for Statistics and Machine Learning. His research has been funded by Microsoft, Facebook, and Google, and has been featured on NPR and in such publications as the New Yorker, the New York Times, and the Wall Street Journal.