Text Analysis with R for Students of Literature (Quantitative Methods in the Humanities and Social Sciences) - Hardcover

Críticas

"I can't think of a more qualified person to guide readers through powerful R techniques for text analysis. While extremely useful for people studying literature, these techniques can be also used by anybody working with texts. Even if you simply want to understand how companies and data scientists are analyzing all kinds of texts, go through this book." (Lev Manovich, Department of Computer Science, The Graduate Center, City University of New York & author of The Language of New Media)

"The open source programming language R has become one of the most central statistical and analytical tool in many sciences. While it has already been used in linguistic applications, this book is the first to discuss the application of (corpus-linguistic and other) methods with R in the context of literary studies. The author covers a wide range of descriptive, analytical, and exploratory methods beautifully and in detail in a book that will appeal to a wide and diverse audience of both students and seasoned researchers from literary studies, linguistic computing, and the digital humanities more generally." (Stefan Th. Gries, Department of Linguistics, University of California, Santa Barbara & author of Quantitative corpus linguistics with R: A Practical Introduction)

"This book does a great service for literary scholars interested in computational approaches to text analysis, giving them ready access to powerful methods for exploring patterns and relationships across l

arge quantities of text. Its clear and lucid explanations will also make it an easy textbook to teach from, especially for instructors with prior background who can then use it as a stepping stone to introducing more complex methods. Amateurs and those with little programming background will find it imminently accessible." (Hoyt Long, Department of East Asian Languages and Civilizations, University of Chicago)

"Through my work as an epidemiologist, I encounter electronic health records in an unstructured form (i.e. text), and Text Analysis with R covers many of the initial steps for studying these records. The book is very accessible; it provides a straightforward introduction to manipulating text information without presuming a background in programming or a familiarity with the jargon used in this field. I also appreciated Jockers' thoughtful inclusion of supplemental explanations and information in footnotes throughout the book. For example, text analysis often involves the use of "regular expressions"; a footnote concisely explains wildcard and escape characters and this explanation spared me a fair bit of confusion in my own work. Although I am not a "student of literature", I thought the book contained many generalizable and expertly-taught lessons that make it a valuable introduction to manipulating and analyzing text." (Matthew Maenner, Ph.D.)

"This book is a worthy introduction to computational text analysis, and it fills an important gap in the literatur

e. It’s very accessible and contains plenty of interesting examples and real applications, which have been collected and crafted over the many years the author taught text analysis to undergraduate and graduate students. Although it focuses on the study of literature, I would highly recommend this book to students in business administration and related fields." (Joao Quariguasi Frota Neto, School of Management, University of Bath)

Reseña del editor

Text Analysis with R for Students of Literature 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 tool kit to include quantitative and computational approaches to the study of text. Computation provides access to information in text that we simply cannot gather using traditional qualitative methods of close reading and human synthesis. Text Analysis with R for Students of Literature provides a practical introduction to computational text analysis using the open source programming language R. R is extremely popular throughout the sciences and because of its accessibility, R is now used increasingly in other research areas. Readers begin working with text right away and each chapter works through a new technique or process such that readers gain a broad exposure to core R procedures and a basic understanding of the possibilities of computational text analysis at both the micro and macro scale. Each chapter builds on the previous as readers move from small scale “microanalysis” of single texts to large scale “macroanalysis” of text corpora, and each chapter 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.