As this operation is expensive a single instance of the word dataframe will be spawned and used throughout the succeeding plots. However, you can also use an additional set of metrics in cases where each document has an associated numeric value describing a certain attribute of the document. Word Cloud is great but I can't figure out how to count the words and the frequency of each word after Word Cloud removes the stop words. WordFrequencyData [word 1 | word 2 | …] gives the total frequencies of all the word i. WordFrequencyData [word, "Total", datespec] gives the total frequency of word for the dates specified by datespec. I have a bunch of text that I'm interested in seeing if there is a trend in the words used. The same lists are available online. This dataset contains the counts of the 333,333 most commonly-used single words on the English language web, as derived from the Google Web Trillion Word Corpus. Frequency lists for BNC World are also published in the book Word Frequencies in Written and Spoken English: based on the British National Corpus by Geoffrey Leech, Paul Rayson, and Andrew Wilson (2001). Up: Contents Possible options include: 3 A third dataset shows the frequency of the word … Visual Word Frequency in the News ... system("ls ../input") ``` ## Tidytext Construction We initially extract the dataset into a counted bag of words. An important set of metrics in text mining relates to the frequency of words (or any token) in a certain corpus of text documents. By default, WordFrequencyData uses the Google Books English n-gram public dataset. 2 Another dataset shows the frequency not only in the eight main genres, but also in nearly 100 "sub-genres" (Magazine-Sports, Newspaper-Finance, Academic-Medical, Web-Reviews, Blogs-Personal, or TV-Comedies, etc).