Plot the results of a "keyword" of features comparing their differential associations with a target and a reference group, after calculating keyness using textstat_keyness().

textplot_keyness(
  x,
  show_reference = TRUE,
  show_legend = TRUE,
  n = 20L,
  min_count = 2L,
  margin = 0.05,
  color = c("darkblue", "gray"),
  labelcolor = "gray30",
  labelsize = 4,
  font = NULL
)

Arguments

x

a return object from textstat_keyness()

show_reference

logical; if TRUE, show key reference features in addition to key target features

show_legend

logical; if TRUE, show legend

n

integer; number of features to plot

min_count

numeric; minimum total count of feature across the target and reference categories, for a feature to be included in the plot

margin

numeric; size of margin where feature labels are shown

color

character or integer; colors of bars for target and reference documents. color must have two elements when show_reference = TRUE. See ggplot2::color.

labelcolor

character; color of feature labels.

labelsize

numeric; size of feature labels and bars. See ggplot2::size.

font

character; font-family of texts. Use default font if NULL.

Value

a ggplot2 object

See also

Author

Haiyan Wang and Kohei Watanabe

Examples

# compare Trump speeches to other Presidents by chi^2 dfmat1 <- data_corpus_inaugural %>% corpus_subset(Year > 1980) %>% dfm(groups = "President", remove = stopwords("english"), remove_punct = TRUE) tstat1 <- textstat_keyness(dfmat1, target = "Trump") textplot_keyness(tstat1, margin = 0.2, n = 10)
# compare contemporary Democrats v. Republicans corp <- data_corpus_inaugural %>% corpus_subset(Year > 1960) docvars(corp, "party") <- ifelse(docvars(corp, "President") %in% c("Nixon", "Reagan", "Bush", "Trump"), "Republican", "Democrat") dfmat2 <- dfm(corp, groups = "party", remove = stopwords("english"), remove_punct = TRUE) tstat2 <- textstat_keyness(dfmat2, target = "Democrat", measure = "lr") textplot_keyness(tstat2, color = c("blue", "red"), n = 10)