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 themicro 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.
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 large 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
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 large 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
"The aim of this book is ... to give the Literature students just the most basic tools needed to do some relatively straightforward textual analysis. ... Even though this is primarily a book intended for literature students, I would actually strongly recommend it to anyone interested in text mining, text analysis and natural language processing. It is a very gentle and approachable introduction to the whole world of textual analysis." (Bojan Tunguz, tunguzreview.com, July, 2015)
"This is a well written book on the topic of Text Analysis. There is enough information to give you a good start using R. Followed by easy to understand details about text analysis. ... This is a good book to have if you are doing text analysis." (Mary Anne, Cats and Dogs with Data, maryannedata.com, August, 2014)
"A remarkably well-crafted book that will allow students to get a quick start and progress toward quite sophisticated text mining tasks. ... exercises provided at the end of each chapter, with solutions at the end of the book, should serve well to help students solidify their knowledge and gain more confidence in their text mining skills. ... a great addition to the libraries of digital humanists and natural language enthusiasts who wish to expand their programming literacy ... ." (Denilson Barbosa, Computing Reviews, August, 2014)
"This is a well written book on the topic of Text Analysis. There is enough information to give you a good start using R. Followed by easy to understand details about text analysis. ... This is a good book to have if you are doing text analysis." (Mary Anne, Cats and Dogs with Data, maryannedata.com, August, 2014)
"A remarkably well-crafted book that will allow students to get a quick start and progress toward quite sophisticated text mining tasks. ... exercises provided at the end of each chapter, with solutions at the end of the book, should serve well to help students solidify their knowledge and gain more confidence in their text mining skills. ... a great addition to the libraries of digital humanists and natural language enthusiasts who wish to expand their programming literacy ... ." (Denilson Barbosa, Computing Reviews, August, 2014)