We generally need to perform some pre-processing of the text data to prepare for the text analysis. Example transformations include converting the text to lower case, removing numbers and punctuation, removing stop words, stemming and identifying synonyms. The basic transforms are all available within .
##  "removeNumbers" "removePunctuation" "removeWords" ##  "stemDocument" "stripWhitespace"
The function tm::tm_map() is used to apply one of these transformations across all documents within a corpus. Other transformations can be implemented using R functions and wrapped within tm::content_transformer() to create a function that can be passed through to tm::tm_map(). We will see an example of that in the next section.
In the following sections we will apply each of the transformations, one-by-one, to remove unwanted characters from the text.
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