Data Analytics

Text as Data: A New Framework for Machine Learning and the Social Sciences

Name: Text as Data: A New Framework for Machine Learning and the Social Sciences
Brand: Princeton University Press
SKU: 9780691207544
Price: 14538.00 INR
Availability: InStock
ISBN: 9780691207544

Contributor(s): Grimmer, Justin Author , Roberts, Margaret E Author , Stewart, Brandon M. Author Format: Hardback

Hardback · ISBN 9780691207544

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Key Specifications

ISBN	9780691207544
Publisher	Princeton University Press
Publication date	March 2022
Language	English
MRP	£92.00 GBP
Page count	360
Item weight	185 g

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. Text as Data shows how to combine new sources of data, machine learning tools, and social science research design to develop and evaluate new insights.

Text as Data is organized around the core tasks in research projects using text--representation, discovery, measurement, prediction, and causal inference. The authors offer a sequential, iterative, and inductive approach to research design. Each research task is presented complete with real-world applications, example methods, and a distinct style of task-focused research.

Bridging many divides--computer science and social science, the qualitative and the quantitative, and industry and academia--Text as Data is an ideal resource for anyone wanting to analyze large collections of text in an era when data is abundant and computation is cheap, but the enduring challenges of social science remain.

Overview of how to use text as data
Research design for a world of data deluge
Examples from across the social sciences and industry

Text as Data: A New Framework for Machine Learning and the Social Sciences

Key Specifications

Grimmer, Justin Author

Roberts, Margaret E Author

Stewart, Brandon M. Author

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