Synopsis
Learn how to conduct a robust text analysis project from start to finish--and then do it again.
Mining is the dominant metaphor in computational text analysis. When mining texts, the implied assumption is that analysts can find kernels of truth--they just have to sift through the rubbish first. In this book, Dustin Stoltz and Marshall Taylor encourage text analysts to work with a different metaphor in mind: mapping. When mapping texts, the goal is not necessarily to find meaningful needles in the haystack, but instead to create reductions of the text to document patterns. Just like with cartographic maps, though, the type and nature of the textual map is dependent on a range of decisions on the part of the researcher. Creating reproducible workflows is therefore critical for the text analyst.
Mapping Texts offers a practical introduction to computational text analysis with step-by-step guides on how to conduct actual text analysis workflows in the R statistical computing environment. The focus is on social science questions and applications, with data ranging from fake news and presidential campaigns to Star Trek and pop stars. The book walks the reader through all facets of a text analysis workflow--from understanding the theories of language embedded in text analysis, all the way to more advanced and cutting-edge techniques.
The book will prove useful not only to social scientists, but anyone interested in conducting text analysis projects.
Les informations fournies dans la section « Synopsis » peuvent faire référence à une autre édition de ce titre.
À propos de l'auteur
Dustin S. Stoltz is an assistant professor of sociology and cognitive science at Lehigh University. His research explores how social structure, culture, and cognition shapes ideas and evaluations.
Marshall A. Taylor is an assistant professor of sociology at New Mexico State University. His research focuses on questions of cognition and measurement in the sociology of culture.
Les informations fournies dans la section « A propos du livre » peuvent faire référence à une autre édition de ce titre.
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Mapping Texts: Computational Text Analysis for the Social Sciences (Computational Social Science)
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Oxford University Press (edition ), 2024
ISBN 10 : 0197756883
ISBN 13 : 9780197756881
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Mapping Texts : Computational Text Analysis for the Social Sciences
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Mapping Texts : Computational Text Analysis for the Social Sciences
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MAPPING TEXTS CPSS P (eng)
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Mapping Texts
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ISBN 13 : 9780197756881
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Paperback. Etat : New. Learn how to conduct a robust text analysis project from start to finish--and then do it again. Mining is the dominant metaphor in computational text analysis. When mining texts, the implied assumption is that analysts can find kernels of truth--they just have to sift through the rubbish first. In this book, Dustin Stoltz and Marshall Taylor encourage text analysts to work with a different metaphor in mind: mapping. When mapping texts, the goal is not necessarily to find meaningful needles in the haystack, but instead to create reductions of the text to document patterns. Just like with cartographic maps, though, the type and nature of the textual map is dependent on a range of decisions on the part of the researcher. Creating reproducible workflows is therefore critical for the text analyst.Mapping Texts offers a practical introduction to computational text analysis with step-by-step guides on how to conduct actual text analysis workflows in the R statistical computing environment. The focus is on social science questions and applications, with data ranging from fake news and presidential campaigns to Star Trek and pop stars. The book walks the reader through all facets of a text analysis workflow--from understanding the theories of language embedded in text analysis, all the way to more advanced and cutting-edge techniques.The book will prove useful not only to social scientists, but anyone interested in conducting text analysis projects. N° de réf. du vendeur LU-9780197756881
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Mapping Texts
Edité par
Oxford University Press Inc, US, 2024
ISBN 10 : 0197756883
ISBN 13 : 9780197756881
Neuf
Paperback
Vendeur : Rarewaves USA, OSWEGO, IL, Etats-Unis
Évaluation du vendeur 5 sur 5 étoiles
Paperback. Etat : New. Learn how to conduct a robust text analysis project from start to finish--and then do it again. Mining is the dominant metaphor in computational text analysis. When mining texts, the implied assumption is that analysts can find kernels of truth--they just have to sift through the rubbish first. In this book, Dustin Stoltz and Marshall Taylor encourage text analysts to work with a different metaphor in mind: mapping. When mapping texts, the goal is not necessarily to find meaningful needles in the haystack, but instead to create reductions of the text to document patterns. Just like with cartographic maps, though, the type and nature of the textual map is dependent on a range of decisions on the part of the researcher. Creating reproducible workflows is therefore critical for the text analyst.Mapping Texts offers a practical introduction to computational text analysis with step-by-step guides on how to conduct actual text analysis workflows in the R statistical computing environment. The focus is on social science questions and applications, with data ranging from fake news and presidential campaigns to Star Trek and pop stars. The book walks the reader through all facets of a text analysis workflow--from understanding the theories of language embedded in text analysis, all the way to more advanced and cutting-edge techniques.The book will prove useful not only to social scientists, but anyone interested in conducting text analysis projects. N° de réf. du vendeur LU-9780197756881
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Mapping Texts (Paperback)
Edité par
Oxford University Press Inc, New York, 2024
ISBN 10 : 0197756883
ISBN 13 : 9780197756881
Neuf
Paperback
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Paperback. Etat : new. Paperback. Learn how to conduct a robust text analysis project from start to finish--and then do it again.Mining is the dominant metaphor in computational text analysis. When mining texts, the implied assumption is that analysts can find kernels of truth--they just have to sift through the rubbish first. In this book, Dustin Stoltz and Marshall Taylor encourage text analysts to work with a different metaphor in mind: mapping. Whenmapping texts, the goal is not necessarily to find meaningful needles in the haystack, but instead to create reductions of the text to document patterns. Just like with cartographic maps, though, the type and nature of thetextual map is dependent on a range of decisions on the part of the researcher. Creating reproducible workflows is therefore critical for the text analyst.Mapping Texts offers a practical introduction to computational text analysis with step-by-step guides on how to conduct actual text analysis workflows in the R statistical computing environment. The focus is on social science questions and applications, with data ranging from fake news and presidential campaignsto Star Trek and pop stars. The book walks the reader through all facets of a text analysis workflow--from understanding the theories of language embedded in text analysis, all the way to more advanced andcutting-edge techniques.The book will prove useful not only to social scientists, but anyone interested in conducting text analysis projects. Mapping Texts is the first introduction to computational text analysis that simultaneously blends conceptual treatments with practical, hands-on examples that walk the reader through how to conduct text analysis projects with real data. The book shows how to conduct text analysis in the R statistical computing environment--a popular programming language in data science. Shipping may be from multiple locations in the US or from the UK, depending on stock availability. N° de réf. du vendeur 9780197756881
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