Internal methods for tokenization providing default and legacy methods for text segmentation.

tokenize_word(x, split_hyphens = FALSE, verbose = quanteda_options("verbose"))

tokenize_word1(x, split_hyphens = FALSE, verbose = quanteda_options("verbose"))

tokenize_character(x, ...)

tokenize_sentence(x, ..., verbose = FALSE)

tokenize_fasterword(x, ...)

tokenize_fastestword(x, ...)

Arguments

x

(named) character; input texts

split_hyphens

logical; if TRUE, split words that are connected by hyphenation and hyphenation-like characters in between words, e.g. "self-aware" becomes c("self", "-", "aware")

verbose

if TRUE, print timing messages to the console

...

used to pass arguments among the functions

Value

a list of characters corresponding to the (most conservative) tokenization, including whitespace where applicable; except for tokenize_word1(), which is a special tokenizer for Internet language that includes URLs, #hashtags, @usernames, and email addresses.

Examples

if (FALSE) { txt <- c(doc1 = "Tweet https://quanteda.io using @quantedainit and #rstats.", doc2 = "The £1,000,000 question.", doc4 = "Line 1.\nLine2\n\nLine3.", doc5 = "?", doc6 = "Self-aware machines! \U0001f600") tokenize_word(txt) tokenize_word(txt, split_hyphens = TRUE) tokenize_word2(txt, split_hyphens = FALSE) tokenize_word2(txt, split_hyphens = TRUE) tokenize_fasterword(txt) tokenize_fastestword(txt) tokenize_sentence(txt) tokenize_character(txt[2]) }