tokenize_internal: quanteda tokenizers

In koheiw/quanteda.core: Quantitative Analysis of Textual Data

Description

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

Usage

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

## Not run: 
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])

## End(Not run)

koheiw/quanteda.core documentation built on Sept. 21, 2020, 3:44 p.m.