27 Text analysis

27.1 Text Mining with R

Julia Silge and David Robinson

This book serves as an introduction of text mining using the tidytext package and other tidy tools in R. The functions provided by the tidytext package are relatively simple; what is important are the possible applications. Thus, this book provides compelling examples of real text mining problems.


27.2 Supervised Machine Learning for Text Analysis in R

Emil Hvitfeldt, Julia Silge

Modeling as a statistical practice can encompass a wide variety of activities. This book focuses on supervised or predictive modeling for text, using text data to make predictions about the world around us. We use the tidymodels framework for modeling, a consistent and flexible collection of R packages developed to encourage good statistical practice.


27.3 Text Mining With Tidy Data Principles

Julia Silge

Text data sets are diverse and ubiquitous, and tidy data principles provide an approach to make text mining easier, more effective, and consistent with tools already in wide use. In this tutorial, you will develop your text mining skills using the tidytext package in R, along with other tidyverse tools.