quanteda (version 2.0.1)

dfm_lookup: Apply a dictionary to a dfm

Description

Apply a dictionary to a dfm by looking up all dfm features for matches in a a set of dictionary values, and replace those features with a count of the dictionary's keys. If exclusive = FALSE then the behaviour is to apply a "thesaurus", where each value match is replaced by the dictionary key, converted to capitals if capkeys = TRUE (so that the replacements are easily distinguished from features that were terms found originally in the document).

Usage

dfm_lookup(
  x,
  dictionary,
  levels = 1:5,
  exclusive = TRUE,
  valuetype = c("glob", "regex", "fixed"),
  case_insensitive = TRUE,
  capkeys = !exclusive,
  nomatch = NULL,
  verbose = quanteda_options("verbose")
)

Arguments

x

the dfm to which the dictionary will be applied

dictionary

a dictionary class object

levels

levels of entries in a hierarchical dictionary that will be applied

exclusive

if TRUE, remove all features not in dictionary, otherwise, replace values in dictionary with keys while leaving other features unaffected

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.

case_insensitive

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

capkeys

if TRUE, convert dictionary keys to uppercase to distinguish them from other features

nomatch

an optional character naming a new feature that will contain the counts of features of x not matched to a dictionary key. If NULL (default), do not tabulate unmatched features.

verbose

print status messages if TRUE

See Also

dfm_replace

Examples

# NOT RUN {
dict <- dictionary(list(christmas = c("Christmas", "Santa", "holiday"),
                          opposition = c("Opposition", "reject", "notincorpus"),
                          taxglob = "tax*",
                          taxregex = "tax.+$",
                          country = c("United_States", "Sweden")))
dfmat <- dfm(c("My Christmas was ruined by your opposition tax plan.",
               "Does the United_States or Sweden have more progressive taxation?"),
             remove = stopwords("english"))
dfmat

# glob format
dfm_lookup(dfmat, dict, valuetype = "glob")
dfm_lookup(dfmat, dict, valuetype = "glob", case_insensitive = FALSE)

# regex v. glob format: note that "united_states" is a regex match for "tax*"
dfm_lookup(dfmat, dict, valuetype = "glob")
dfm_lookup(dfmat, dict, valuetype = "regex", case_insensitive = TRUE)

# fixed format: no pattern matching
dfm_lookup(dfmat, dict, valuetype = "fixed")
dfm_lookup(dfmat, dict, valuetype = "fixed", case_insensitive = FALSE)

# show unmatched tokens
dfm_lookup(dfmat, dict, nomatch = "_UNMATCHED")

# }