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Text als Daten: Ein neuer Rahmen für maschinelles Lernen und die Sozialwissenschaften, düster
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Text als Daten: Ein neuer Rahmen für maschinelles Lernen und die Sozialwissenschaften, düster

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    Zuletzt aktualisiert am 11. Sep. 2025 15:25:14 MESZAlle Änderungen ansehenAlle Änderungen ansehen

    Artikelmerkmale

    Artikelzustand
    Sehr gut: Buch, das nicht neu aussieht und gelesen wurde, sich aber in einem hervorragenden Zustand ...
    ISBN
    9780691207551
    Kategorie

    Über dieses Produkt

    Product Identifiers

    Publisher
    Princeton University Press
    ISBN-10
    0691207550
    ISBN-13
    9780691207551
    eBay Product ID (ePID)
    23050091518

    Product Key Features

    Number of Pages
    360 Pages
    Publication Name
    Text As Data : a New Framework for Machine Learning and the Social Sciences
    Language
    English
    Subject
    Methodology, Data Modeling & Design, General, Databases / Data Mining
    Publication Year
    2022
    Type
    Textbook
    Subject Area
    Mathematics, Computers, Social Science
    Author
    Margaret E. Roberts, Brandon M. Stewart, Justin Grimmer
    Format
    Trade Paperback

    Dimensions

    Item Height
    0.7 in
    Item Weight
    23.4 Oz
    Item Length
    10 in
    Item Width
    7 in

    Additional Product Features

    Intended Audience
    College Audience
    LCCN
    2022-279056
    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 Edition
    23
    Illustrated
    Yes
    Dewey Decimal
    006.3/12
    Synopsis
    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 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 Number
    QA76.9.D343

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