The digital humanities produces many forms of scholarship in different mediums; while a significant part is digital and mostly online in 2014, in many cases, the tangible vehicle of that scholarship is in print. Text Analysis with R for Students of Literature is a book by Matthew Jockers, co-founder of the Stanford Literary Lab with Franco Moretti, and currently professor in the English Department at the University of Nebraska-Lincoln. The book is a primer on the use of computational techniques—in particular the use of the R programming language—for the study of literature and literary history. The book follows on the success of Jocker’s 2013 volume Macronalysis: Digital Methods and Literary History, and serves as it’s practical companion.

The book also serves as a great introduction to key concepts and techniques in one of the most important strands of the history of digital humanities: humanities computing. Text Analysis with R is divided into three parts: Microanalysis (the study of one text, Moby Dick), Mesoanalysis (the study of a small corpus) and Macroanalysis (the study of a large corpus). Jockers writes in a very accessible style making it great for students and beginners. As Jockers puts it in the Introduction:

[This book] is designed for the student and scholar of literature who doesn’t already know a programming language, or at the every least does not know the R language, and more importantly is a person who has come to R because of some literary question or due to some sense that computation might offer a new or particularly useful way to address, explore, probe, or answer some literary question. You are not coming to this book because you want to become a master programmer. You are a student or scholar in the humanities seeking to learn just enough to gain entry into the wide world of humanities computing.

While we encourage you to get a copy of the book, Springer is kind enough to offer a version online.

Link: http://www.matthewjockers.net/text-analysis-with-r-for-students-of-literature/

Selected by: Alex Gil

Text by: Alex Gil