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Text analysis with R: for students of literature

Now in its second edition, Text Analysis with R provides a practical introduction to computational text analysis using the open source programming language R. R is an extremely popular programming language, used throughout the sciences; due to its accessibility, R is now used increasingly in other r...

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Detalles Bibliográficos
Autores principales: Jockers, Matthew L, Thalken, Rosamond
Lenguaje:eng
Publicado: Springer 2020
Materias:
Acceso en línea:https://dx.doi.org/10.1007/978-3-030-39643-5
http://cds.cern.ch/record/2717227
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author Jockers, Matthew L
Thalken, Rosamond
author_facet Jockers, Matthew L
Thalken, Rosamond
author_sort Jockers, Matthew L
collection CERN
description Now in its second edition, Text Analysis with R provides a practical introduction to computational text analysis using the open source programming language R. R is an extremely popular programming language, used throughout the sciences; due to its accessibility, R is now used increasingly in other research areas. In this volume, readers immediately begin working with text, and each chapter examines a new technique or process, allowing readers to obtain a broad exposure to core R procedures and a fundamental understanding of the possibilities of computational text analysis at both the micro and the macro scale. Each chapter builds on its predecessor as readers move from small scale “microanalysis” of single texts to large scale “macroanalysis” of text corpora, and each concludes with a set of practice exercises that reinforce and expand upon the chapter lessons. The book’s focus is on making the technical palatable and making the technical useful and immediately gratifying. Text Analysis with R is written with students and scholars of literature in mind but will be applicable to other humanists and social scientists wishing to extend their methodological toolkit to include quantitative and computational approaches to the study of text. Computation provides access to information in text that readers simply cannot gather using traditional qualitative methods of close reading and human synthesis. This new edition features two new chapters: one that introduces dplyr and tidyr in the context of parsing and analyzing dramatic texts to extract speaker and receiver data, and one on sentiment analysis using the syuzhet package. It is also filled with updated material in every chapter to integrate new developments in the field, current practices in R style, and the use of more efficient algorithms.
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spelling cern-27172272021-04-21T18:08:00Zdoi:10.1007/978-3-030-39643-5http://cds.cern.ch/record/2717227engJockers, Matthew LThalken, RosamondText analysis with R: for students of literatureMathematical Physics and MathematicsNow in its second edition, Text Analysis with R provides a practical introduction to computational text analysis using the open source programming language R. R is an extremely popular programming language, used throughout the sciences; due to its accessibility, R is now used increasingly in other research areas. In this volume, readers immediately begin working with text, and each chapter examines a new technique or process, allowing readers to obtain a broad exposure to core R procedures and a fundamental understanding of the possibilities of computational text analysis at both the micro and the macro scale. Each chapter builds on its predecessor as readers move from small scale “microanalysis” of single texts to large scale “macroanalysis” of text corpora, and each concludes with a set of practice exercises that reinforce and expand upon the chapter lessons. The book’s focus is on making the technical palatable and making the technical useful and immediately gratifying. Text Analysis with R is written with students and scholars of literature in mind but will be applicable to other humanists and social scientists wishing to extend their methodological toolkit to include quantitative and computational approaches to the study of text. Computation provides access to information in text that readers simply cannot gather using traditional qualitative methods of close reading and human synthesis. This new edition features two new chapters: one that introduces dplyr and tidyr in the context of parsing and analyzing dramatic texts to extract speaker and receiver data, and one on sentiment analysis using the syuzhet package. It is also filled with updated material in every chapter to integrate new developments in the field, current practices in R style, and the use of more efficient algorithms.Springeroai:cds.cern.ch:27172272020
spellingShingle Mathematical Physics and Mathematics
Jockers, Matthew L
Thalken, Rosamond
Text analysis with R: for students of literature
title Text analysis with R: for students of literature
title_full Text analysis with R: for students of literature
title_fullStr Text analysis with R: for students of literature
title_full_unstemmed Text analysis with R: for students of literature
title_short Text analysis with R: for students of literature
title_sort text analysis with r: for students of literature
topic Mathematical Physics and Mathematics
url https://dx.doi.org/10.1007/978-3-030-39643-5
http://cds.cern.ch/record/2717227
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