Customer Reviews

Quantitative Corpus Linguistics with R: A Practical Introduction

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I evaluated this book for use in my course in quantitative corpus linguistics and decided not to use it. The problem is not with the content, which is impressive; Gries knows his stuff and I learned a lot. Unfortunately, the format, structure, and execution of this book are seriously botched, and in the end I didn't want to subject my students to the pain that I suffered having to read it. Here are the major problems: (1) The exercise boxes promised in the introduction are inexplicably missing from the text (you need to go to the web site to find them). (2) The typeface is painfully tiny. (3) Some chapters are way too long (Chapter 3 is close to 100 pages, almost half the book). (4) The R code listings are even more unreadable than normal because all the whitespace has been replaced, for no good reason (R ignores whitespace), with gigantic black dots. (5) The index is one of the worst I've ever seen; for example, you won't find "bigram" or "ordinal" in the index, but the entry for "retrieve/search" (whatever that means) points to almost 100 pages. Linguists who want a general introduction to quantitative methods (not specific to corpora) would be much better off with the excellent texts from Johnson or Baayen.

This book was not just written, it was designed--and well designed to teach readers about both corpus linguistics and the R statistics package. This electronic version allows busy readers with Kindles or iPhones to study productively during long commutes, even longer delays at the doctor's office, and endless unpunctuated speeches by boorish colleagues in staff meeting.

The six chapters of Stephan Th. Gries' book unfold in an instructionally sound sequence. Chapter 1 briefly introduces corpus linguistics and directs readers elsewhere for a thorough treatment of its history and theories. The second chapter defines word frequency lists, word collocations, and concordances--three basic analysis tools of the discipline. Chapter 3 shifts focus and introduces the R software. This is an excellent and thorough coverage of R data manipulation, programming, and the text processing needed to analyze linguistic corpora.

Building on this foundation, the book integrates R with linguistic analysis. Chapter 4 revisits word lists, collocations and concordances, teaching readers to implement these methods in R. Chapter 5 reviews the basics of statistical reasoning and introduces additional analysis techniques in R. Chapter 6 presents case studies and points readers to the book's supporting web site for associated data files and R syntax files.

The book is considerate of the reader. It uses only freely-available, open source software such as R, the Tinn-R text editor, and OpenOffice Calc. Beyond the price of the book and access to a computer, the author intends no financial barriers to learning. The micro-design of the chapters is also reader-friendly. R code and output are clearly marked and helpfully annotated. Frequent "Think Breaks" in the chapters challenge readers to solve a small problem before reading the answer. This technique encourages active reading and produces a feeling of satisfaction as one progresses through each section. Chapters end with "For further study/exploration" sections that contain pointers to R documentation, web resources, and further reading.

I recommend this book as a self-contained source about statistical methods in corpus linguistics as implemented in R. I would supplement it with Svenja Adolphs' Introducing Electronic Text Analysis to learn how the results of statistical analysis are used in applied linguistics and related disciplines.

If you already work with Corpus Linguistics or plan on doing so, this is a book you MUST have, read thoroughly and ensure its application. The use of R as a tool to both manipulate and analyze corpus data is surely an important step towards a more systematic and more quantitatively-oriented CL. Sure enough, this book is the biggest contribution towards this end thus far!

I have only started reading the book, but it seems like it will be very helpful for my dissertation analyses. I have never used R before, but with the book instructions, I have been able to understand basic commands. I'm not yet far enough to see how easy useful commands will be, but things so far are very well explained. I do have a background in computer science and linguistics, but I haven't used many scripting languages and certainly not for a long time.

When I started reading this book, I knew nothing about R but I was able to follow every single paragraph and example, as all the steps are clearly explained and nothing is taken for granted. Also, the exercises found in the companion website are of great help to acquire the needed practice. This is the perfect textbook for any introductory course to applied corpus linguistics or empirical linguistics.