rainette (version 0.1.2)

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"),
  n_terms = 15,
  show_negative = TRUE,
  max_p = 0.05
)

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

Value

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

See Also

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

Examples

# NOT RUN {
library(quanteda)
corpus <- data_corpus_inaugural
corpus <- head(corpus, n = 10)
corpus <- split_segments(corpus)
dtm <- dfm(corpus, remove = stopwords("en"), tolower = TRUE, remove_punct = TRUE)
dtm <- dfm_trim(dtm, min_termfreq = 3)
res <- rainette(dtm, k = 3)
groups <- cutree_rainette(res, k = 3)
rainette_stats(groups, dtm)
# }