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Text as data :a new framework for machine learning and the social sciences /

紀錄類型:	書目-語言資料,印刷品 : 單行本
正題名/作者:	Text as data :/ Justin Grimmer, Margaret E. Roberts, Brandon M. Stewart.
其他題名:	a new framework for machine learning and the social sciences /
作者:	Grimmer, Justin.
其他作者:	Roberts, Margaret E.
出版者:	Princeton, New Jersey :Princeton University Press,c2022.
面頁冊數:	xix, 336 p. :ill. ;26 cm.
標題:	Text data mining. -
ISBN:	9780691207551
ISBN:	0691207542
ISBN:	0691207550
ISBN:	9780691207544

Text as data :a new framework for machine learning and the social sciences /
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100 1 $a Grimmer, Justin. $3 1000147936
245 1 0 $a Text as data : $b a new framework for machine learning and the social sciences / $c Justin Grimmer, Margaret E. Roberts, Brandon M. Stewart.
260 $a Princeton, New Jersey : $b Princeton University Press, $c c2022.
300 $a xix, 336 p. : $b ill. ; $c 26 cm.
504 $a Includes bibliographical references (p. [307]-329) and index.
520 $a "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." -- publisher.
650 0 $a Text data mining. $3 1000147939
650 0 $a Social sciences $x Data processing. $3 189014
650 0 $a Machine learning. $3 147118
700 1 $a Roberts, Margaret E. $3 1000147937
700 1 $a Stewart, Brandon M. $3 1000147938