Text as Data
A New Framework for Machine Learning and the Social Sciences
$131.89
- Paperback
360 pages
- Release Date
6 June 2022
Summary
Text as Data: A Guide for Using Computational Text Analysis to Learn About the Social World
From social media posts and text messages to digital government documents and archives, researchers are bombarded with a deluge of text reflecting the social world. This textual data gives unprecedented insights into fundamental questions in the social sciences, humanities, and industry. Meanwhile, new machine learning tools are rapidly transforming the way science and business are conducted.…
Book Details
| ISBN-13: | 9780691207551 |
|---|---|
| ISBN-10: | 0691207550 |
| Author: | Justin Grimmer, Brandon M. Stewart, Margaret E. Roberts |
| Publisher: | Princeton University Press |
| Imprint: | Princeton University Press |
| Format: | Paperback |
| Number of Pages: | 360 |
| Release Date: | 6 June 2022 |
| Weight: | 666g |
| Dimensions: | 254mm x 178mm |
What They're Saying
Critics Review
“Among the metaverse of possible books on Text as Data that could have been published … I was pleased that my universe produced this one. I will assign this book as a critical part of my own course on content analysis for years to come, and it has already altered and improved the coherence of my own vocabulary and articulation for several critical choices underlying the process of turning text into data… . Highly recommend.”—James Evans, Sociological Methods & Research
About The Author
Justin Grimmer
Justin Grimmer is professor of political science and a senior fellow at the Hoover Institution at Stanford University. Twitter @justingrimmer
Margaret E. Roberts is associate professor in political science and the Halcolu Data Science Institute at the University of California, San Diego. Twitter @mollyeroberts
Brandon M. Stewart is assistant professor of sociology and Arthur H. Scribner Bicentennial Preceptor at Princeton University. Twitter @b_m_stewart
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