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An innovative and accessible guide to doing social research in the digital age

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 impotant ideas with examples of outstanding research
  • Combines ideas from social science and data science in an accessible style
  • 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 activites for the classroom or self-study
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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.