Text Mining with R

Much of the data available today is unstructured and text-heavy, making it challenging for analysts to apply their usual data wrangling and visualization tools. With this practical book Text Mining with R, you’ll explore text-mining techniques with tidytext, a package that authors Julia Silge and David Robinson developed using the tidy principles behind R packages like ggraph and dplyr. You’ll learn how tidytext and other tidy tools in R can make text analysis easier and more effective.

Book Description

Topics included: The Tidy Text Format • Sentiment Analysis with Tidy Data • Analyzing Word and Document Frequency: tf-idf • Relationships Between Words: N-grams and Correlations • Converting to and from Nontidy Formats • Topic Modeling • Case Study: Comparing Twitter Archives • Case Study: Mining NASA Metadata • Case Study: Analyzing Usenet Text

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