num_pages: 194
description: 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 youll 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 . Youll learn how tidytext and other tidy tools in R can make text analysis easier and more effective. The authors demonstrate how treating text as data frames enables you to manipulate summarize and visualize characteristics of text. Youll also learn how to integrate natural language processing (NLP) into effective workflows. Practical code examples and data explorations will help you generate real insights from literature news and social media.
language: English
title: Text Mining with R: A Tidy Approach
publisher: O'Reilly Media