Text Analysis with R for Students of Literature

(This article was first published on Pachá (Batteries Included), and kindly contributed to R-bloggers)

About the book

I obtained a copy of this book by Matthew Jockers throughout Universities’ access from Springer. You can also get a copy from Amazon.

This book is short and to the point. I would actually strongly recommend it to anyone interested in text mining and natural language processing.

What I do like the most about this book? That you can download the exercises from the book’s website. I downloaded the zip, extracted the folder and then created a RStudio project to the folder and that’s it. Then I could follow the explanations without needing to transcript the code from the pdf. Amazing!

Table of contents

I couldn’t find it full on the web so I write it here:

Part Contents
Part I Microanalysis R Basics
First Foray into Text Analysis with R
Accessing and Comparing Word Frequency Data
Token Distribution Analysis
Part II Mesoanalysis Measures of Lexical Variety
Hapax Richness
Do It KWIC (Better)
Part III Macroanalysis Clustering
Topic Modeling

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