quanteda.textplots (version 0.95)

textplot_wordcloud: Plot features as a wordcloud

Description

Plot a dfm or quanteda.textstats::textstat_keyness object as a wordcloud, where the feature labels are plotted with their sizes proportional to their numerical values in the dfm. When comparison = TRUE, it plots comparison word clouds by document (or by target and reference categories in the case of a keyness object).

Usage

textplot_wordcloud(
  x,
  min_size = 0.5,
  max_size = 4,
  min_count = 3,
  max_words = 500,
  color = "darkblue",
  font = NULL,
  adjust = 0,
  rotation = 0.1,
  random_order = FALSE,
  random_color = FALSE,
  ordered_color = FALSE,
  labelcolor = "gray20",
  labelsize = 1.5,
  labeloffset = 0,
  fixed_aspect = TRUE,
  ...,
  comparison = FALSE
)

Arguments

x

a dfm or quanteda.textstats::textstat_keyness object

min_size

size of the smallest word

max_size

size of the largest word

min_count

words with frequency below min_count will not be plotted

max_words

maximum number of words to be plotted. The least frequent terms dropped. The maximum frequency will be split evenly across categories when comparison = TRUE.

color

colour of words from least to most frequent

font

font-family of words and labels. Use default font if NULL.

adjust

adjust sizes of words by a constant. Useful for non-English words for which R fails to obtain correct sizes.

rotation

proportion of words with 90 degree rotation

random_order

plot words in random order. If FALSE, they will be plotted in decreasing frequency.

random_color

choose colours randomly from the colours. If FALSE, the colour is chosen based on the frequency

ordered_color

if TRUE, then colours are assigned to words in order.

labelcolor

colour of group labels. Only used when comparison = TRUE.

labelsize

size of group labels. Only used when comparison = TRUE.

labeloffset

position of group labels. Only used when comparison = TRUE.

fixed_aspect

logical; if TRUE, the aspect ratio is fixed. Variable aspect ratio only supported if rotation = 0.

...

additional parameters. Only used to make it compatible with wordcloud

comparison

logical; if TRUE, plot a wordcloud that compares documents in the same way as wordcloud::comparison.cloud(). If x is a quanteda.textstats::textstat_keyness object, then only the target category's key terms are plotted when comparison = FALSE, otherwise the top max_words / 2 terms are plotted from the target and reference categories.

Author

Kohei Watanabe, building on code from Ian Fellows's wordcloud package.

Details

The default is to plot the word cloud of all features, summed across documents. To produce word cloud plots for specific document or set of documents, you need to slice out the document(s) from the dfm object.

Comparison wordcloud plots may be plotted by setting comparison = TRUE, which plots a separate grouping for each document in the dfm. This means that you will need to slice out just a few documents from the dfm, or to create a dfm where the "documents" represent a subset or a grouping of documents by some document variable.

Examples

# plot the features (without stopwords) from Obama's inaugural addresses
set.seed(10)
library("quanteda")
dfmat1 <- data_corpus_inaugural |>
    corpus_subset(President == "Obama") |>
    tokens(remove_punct = TRUE) |>
    tokens_remove(stopwords("en")) |>
    dfm() |>
    dfm_trim(min_termfreq = 3)

# basic wordcloud
textplot_wordcloud(dfmat1)

# plot in colours with some additional options
textplot_wordcloud(dfmat1, rotation = 0.25,
                   color = rev(RColorBrewer::brewer.pal(10, "RdBu")))

# other display options
col <- sapply(seq(0.1, 1, 0.1), function(x) adjustcolor("#1F78B4", x))
textplot_wordcloud(dfmat1, adjust = 0.5, random_order = FALSE,
                   color = col, rotation = FALSE)

# comparison plot of Obama v. Trump
dfmat2 <- data_corpus_inaugural |>
    corpus_subset(President %in% c("Obama", "Trump")) |>
    tokens(remove_punct = TRUE) |>
    tokens_remove(stopwords("en")) |>
    dfm()
dfmat2 <- dfm_group(dfmat2, dfmat2$President) |>
    dfm_trim(min_termfreq = 3)

textplot_wordcloud(dfmat2, comparison = TRUE, max_words = 100,
                   color = c("blue", "red"))

if (FALSE) {
# for keyness
tstat <- data_corpus_inaugural[c(1, 3)] |>
    tokens(remove_punct = TRUE) |>
    tokens_remove(stopwords("en")) |>
    dfm() |>
    quanteda.textstats::textstat_keyness()
textplot_wordcloud(tstat, min_count = 2)
textplot_wordcloud(tstat, min_count = 2, comparison = FALSE)
}