Text mining, the tidy way
Unstructured, text-heavy data sets are increasingly important in many domains, and tidy data principles and tidy tools can make text mining easier and more effective.
We introduce the tidytext package for approaching text analysis from a tidy data perspective.
We can manipulate, summarize, and visualize the characteristics of text using the R tidy tool ecosystem; these tools extend naturally to many text analyses and allow analysts to integrate natural language processing into effective workflows already in wide use.
We explore how to implement approaches such as sentiment analysis of texts and measuring tf-idf to quantify what a document is about.
Source: useR 2017
We introduce the tidytext package for approaching text analysis from a tidy data perspective.
We can manipulate, summarize, and visualize the characteristics of text using the R tidy tool ecosystem; these tools extend naturally to many text analyses and allow analysts to integrate natural language processing into effective workflows already in wide use.
We explore how to implement approaches such as sentiment analysis of texts and measuring tf-idf to quantify what a document is about.
Source: useR 2017