quanteda (version 2.0.1)

tokens_compound: Convert token sequences into compound tokens

Description

Replace multi-token sequences with a multi-word, or "compound" token. The resulting compound tokens will represent a phrase or multi-word expression, concatenated with concatenator (by default, the "_" character) to form a single "token". This ensures that the sequences will be processed subsequently as single tokens, for instance in constructing a dfm.

Usage

tokens_compound(
  x,
  pattern,
  concatenator = "_",
  valuetype = c("glob", "regex", "fixed"),
  window = 0,
  case_insensitive = TRUE,
  join = TRUE
)

Arguments

x

an input tokens object

pattern

a character vector, list of character vectors, dictionary, or collocations object. See pattern for details.

concatenator

the concatenation character that will connect the words making up the multi-word sequences. The default _ is recommended since it will not be removed during normal cleaning and tokenization (while nearly all other punctuation characters, at least those in the Unicode punctuation class [P] will be removed).

valuetype

the type of pattern matching: "glob" for "glob"-style wildcard expressions; "regex" for regular expressions; or "fixed" for exact matching. See valuetype for details.

window

integer; a vector of length 1 or 2 that specifies size of the window of tokens adjacent to pattern that will be compounded with matches to pattern. The window can be asymmetric if two elements are specified, with the first giving the window size before pattern and the second the window size after. If paddings (empty "" tokens) are found, window will be shrunk to exclude them.

case_insensitive

logical; if TRUE, ignore case when matching a pattern or dictionary values

join

logical; if TRUE, join overlapping compounds into a single compound; otherwise, form these separately. See examples.

Value

A tokens object in which the token sequences matching pattern have been replaced by new compounded "tokens" joined by the concatenator.

Examples

# NOT RUN {
txt <- "The United Kingdom is leaving the European Union."
toks <- tokens(txt, remove_punct = TRUE)

# character vector - not compounded
tokens_compound(toks, c("United", "Kingdom", "European", "Union"))

# elements separated by spaces - not compounded
tokens_compound(toks, c("United Kingdom", "European Union"))

# list of characters - is compounded
tokens_compound(toks, list(c("United", "Kingdom"), c("European", "Union")))

# elements separated by spaces, wrapped in phrase)() - is compounded
tokens_compound(toks, phrase(c("United Kingdom", "European Union")))

# supplied as values in a dictionary (same as list) - is compounded
# (keys do not matter)
tokens_compound(toks, dictionary(list(key1 = "United Kingdom",
                                      key2 = "European Union")))
# pattern as dictionaries with glob matches
tokens_compound(toks, dictionary(list(key1 = c("U* K*"))), valuetype = "glob")

# supplied as collocations - is compounded
colls <- tokens("The new European Union is not the old European Union.") %>%
    textstat_collocations(size = 2, min_count = 1, tolower = FALSE)
tokens_compound(toks, colls, case_insensitive = FALSE)

# note the differences caused by join = FALSE
compounds <- list(c("the", "European"), c("European", "Union"))
tokens_compound(toks, pattern = compounds, join = TRUE)
tokens_compound(toks, pattern = compounds, join = FALSE)

# use window to form ngrams
tokens_remove(toks, pattern = stopwords("en")) %>%
    tokens_compound(pattern = "leav*", join = FALSE, window = c(0, 3))

# }