MOMENTAN AUSVERKAUFT
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Product Identifiers
PublisherPrinceton University Press
ISBN-100691207550
ISBN-139780691207551
eBay Product ID (ePID)23050091518
Product Key Features
Number of Pages360 Pages
Publication NameText As Data : a New Framework for Machine Learning and the Social Sciences
LanguageEnglish
SubjectMethodology, Data Modeling & Design, General, Databases / Data Mining
Publication Year2022
TypeTextbook
Subject AreaMathematics, Computers, Social Science
AuthorMargaret E. Roberts, Brandon M. Stewart, Justin Grimmer
FormatTrade Paperback
Dimensions
Item Height0.7 in
Item Weight23.4 Oz
Item Length10 in
Item Width7 in
Additional Product Features
Intended AudienceCollege Audience
LCCN2022-279056
Reviews"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
Dewey Edition23
IllustratedYes
Dewey Decimal006.3/12
SynopsisA 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 organised 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 analyse 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, 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, 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
LC Classification NumberQA76.9.D343
