rainette (version 0.3.1.1)

rainette_stats: Generate cluster keyness statistics from a rainette result

Description

Generate cluster keyness statistics from a rainette result

Usage

rainette_stats(
  groups,
  dtm,
  measure = c("chi2", "lr", "frequency", "docprop"),
  n_terms = 15,
  show_negative = TRUE,
  max_p = 0.05
)

Value

A list with, for each group, a data.frame of keyness statistics for the most specific n_terms features.

Arguments

groups

groups membership computed by cutree_rainette or cutree_rainette2

dtm

the dfm object used to compute the clustering

measure

statistics to compute

n_terms

number of terms to display in keyness plots

show_negative

if TRUE, show negative keyness features

max_p

maximum keyness statistic p-value

See Also

quanteda.textstats::textstat_keyness(), rainette_explor(), rainette_plot()

Examples

# \donttest{
require(quanteda)
corpus <- data_corpus_inaugural
corpus <- head(corpus, n = 10)
corpus <- split_segments(corpus)
tok <- tokens(corpus, remove_punct = TRUE)
tok <- tokens_remove(tok, stopwords("en"))
dtm <- dfm(tok, tolower = TRUE)
dtm <- dfm_trim(dtm, min_docfreq = 3)
res <- rainette(dtm, k = 3, min_segment_size = 15)
groups <- cutree_rainette(res, k = 3)
rainette_stats(groups, dtm)
# }