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Text as Data
A New Framework for Machine Learning and the Social Sciences
Taschenbuch von Justin Grimmer (u. a.)
Sprache: Englisch

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Beschreibung
"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 [...] 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." --Page 4 of cover.
"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 [...] 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." --Page 4 of cover.
Über den Autor
Justin Grimmer, Margaret E. Roberts, and Brandon M. Stewart
Details
Erscheinungsjahr: 2022
Genre: Importe, Informatik
Rubrik: Naturwissenschaften & Technik
Medium: Taschenbuch
Inhalt: Kartoniert / Broschiert
ISBN-13: 9780691207551
ISBN-10: 0691207550
Sprache: Englisch
Einband: Kartoniert / Broschiert
Autor: Grimmer, Justin
Roberts, Margaret E
Stewart, Brandon M
Hersteller: Princeton University Press
Verantwortliche Person für die EU: Produktsicherheitsverantwortliche/r, Europaallee 1, D-36244 Bad Hersfeld, gpsr@libri.de
Maße: 251 x 178 x 21 mm
Von/Mit: Justin Grimmer (u. a.)
Erscheinungsdatum: 29.03.2022
Gewicht: 0,722 kg
Artikel-ID: 119929251
Über den Autor
Justin Grimmer, Margaret E. Roberts, and Brandon M. Stewart
Details
Erscheinungsjahr: 2022
Genre: Importe, Informatik
Rubrik: Naturwissenschaften & Technik
Medium: Taschenbuch
Inhalt: Kartoniert / Broschiert
ISBN-13: 9780691207551
ISBN-10: 0691207550
Sprache: Englisch
Einband: Kartoniert / Broschiert
Autor: Grimmer, Justin
Roberts, Margaret E
Stewart, Brandon M
Hersteller: Princeton University Press
Verantwortliche Person für die EU: Produktsicherheitsverantwortliche/r, Europaallee 1, D-36244 Bad Hersfeld, gpsr@libri.de
Maße: 251 x 178 x 21 mm
Von/Mit: Justin Grimmer (u. a.)
Erscheinungsdatum: 29.03.2022
Gewicht: 0,722 kg
Artikel-ID: 119929251
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