Bit by Bit: Social Research in the Digital Age

Bit by Bit: Social Research in the Digital Age

by Matthew J. Salganik
Bit by Bit: Social Research in the Digital Age

Bit by Bit: Social Research in the Digital Age

by Matthew J. Salganik

eBookCore Textbook (Core Textbook)

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Overview

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 before imaginable, offering entirely new approaches to core questions about social behavior. Bit by Bit is the key to unlocking these powerful methods—a landmark book that will fundamentally change how the next generation of social scientists and data scientists explores the world around us.

Bit by Bit is the essential guide to mastering the key principles of doing social research in this fast-evolving digital age. In this comprehensive yet accessible book, Matthew Salganik explains how the digital revolution is transforming how social scientists observe behavior, ask questions, run experiments, and engage in mass collaborations. He provides a wealth of real-world examples throughout and also lays out a principles-based approach to handling ethical challenges.

Bit by Bit is an invaluable resource for social scientists who want to harness the research potential of big data and a must-read for data scientists interested in applying the lessons of social science to tomorrow’s technologies.

  • Illustrates important ideas with examples of outstanding research
  • Combines ideas from social science and data science in an accessible style and without jargon
  • Goes beyond the analysis of “found” data to discuss the collection of “designed” data such as surveys, experiments, and mass collaboration
  • Features an entire chapter on ethics
  • Includes extensive suggestions for further reading and activities for the classroom or self-study

Product Details

ISBN-13: 9781400888184
Publisher: Princeton University Press
Publication date: 11/27/2017
Sold by: Barnes & Noble
Format: eBook
Pages: 448
File size: 18 MB
Note: This product may take a few minutes to download.

About the Author

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.

Table of Contents

Preface xv
1 Introduction 1
2 Observing Behavior 13
3 Asking Questions 85
4 Running Experiments 147
5 Creating Mass Collaboration 231
6 Ethics 281
7 The Future 355
Acknowledgments 361
References 367
Index 413

What People are Saying About This

From the Publisher

"An enticing and important field guide to the new frontier of digital social research."—Beth Simone Noveck, Forbes

"Salganik is one of the first natural-born computational social scientists. . . . 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

"A tremendously useful introduction for data scientists to the pressing questions of the social sciences, and for social scientists to the mindset and toolset of data science. With skill and scholarly insight, Salganik addresses the ethical questions that arise at the intersection of data science and social science."—Chris Wiggins, Columbia University

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