Get the features from a document-feature matrix, which are stored as the column names of the dfm object.
featnames(x)the dfm whose features will be extracted
character vector of the feature labels
dfmat <- dfm(tokens(data_corpus_inaugural))
# first 50 features (in original text order)
head(featnames(dfmat), 50)
#> [1] "fellow-citizens" "of" "the" "senate"
#> [5] "and" "house" "representatives" ":"
#> [9] "among" "vicissitudes" "incident" "to"
#> [13] "life" "no" "event" "could"
#> [17] "have" "filled" "me" "with"
#> [21] "greater" "anxieties" "than" "that"
#> [25] "which" "notification" "was" "transmitted"
#> [29] "by" "your" "order" ","
#> [33] "received" "on" "14th" "day"
#> [37] "present" "month" "." "one"
#> [41] "hand" "i" "summoned" "my"
#> [45] "country" "whose" "voice" "can"
#> [49] "never" "hear"
# first 50 features alphabetically
head(sort(featnames(dfmat)), 50)
#> [1] "!" "\"" "$" "'" "("
#> [6] ")" "," "-" "." "/"
#> [11] "1" "1,000" "100" "100,000,000" "108"
#> [16] "11" "120,000,000" "125" "13" "14th"
#> [21] "15th" "16" "1774" "1776" "1778"
#> [26] "1780" "1787" "1789" "1790" "1800"
#> [31] "1801" "1812" "1815" "1816" "1817"
#> [36] "1818" "1826" "1850" "1861" "1863"
#> [41] "1868" "1873" "1880" "1886" "1890"
#> [46] "1893" "1896" "1897" "1898" "1899"
# contrast with descending total frequency order from topfeatures()
names(topfeatures(dfmat, 50))
#> [1] "the" "of" "," "and" "."
#> [6] "to" "in" "a" "our" "we"
#> [11] "that" "be" "is" "it" "for"
#> [16] "by" "have" "which" "not" "with"
#> [21] "as" "will" "this" "i" "all"
#> [26] "are" "their" "but" "has" "people"
#> [31] "from" "its" ";" "government" "or"
#> [36] "on" "my" "us" "been" "can"
#> [41] "no" "they" "-" "so" "an"
#> [46] "who" "must" "upon" "at" "great"