Plot features as a wordcloud — textplot

Plot a dfm or 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).

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 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	color 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 colors randomly from the colors. If `FALSE`, the color is chosen based on the frequency
ordered_color	if `TRUE`, then colors are assigned to words in order.
labelcolor	color 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 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.

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.

Author

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

Examples

# plot the features (without stopwords) from Obama's inaugural addresses
set.seed(10)
dfmat1 <- dfm(corpus_subset(data_corpus_inaugural, President == "Obama"),
              remove = stopwords("english"), remove_punct = TRUE) %>%
   dfm_trim(min_termfreq = 3)
    
# basic wordcloud
textplot_wordcloud(dfmat1)

# plot in colors 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 <- dfm(corpus_subset(data_corpus_inaugural, President %in% c("Obama", "Trump")),
              remove = stopwords("english"), remove_punct = TRUE, groups = "President") %>%
    dfm_trim(min_termfreq = 3)

textplot_wordcloud(dfmat2, comparison = TRUE, max_words = 300,
                   color = c("blue", "red"))
                   
# for keyness
tstat <- tail(data_corpus_inaugural, 2) %>%
    dfm(remove_punct = TRUE, remove = stopwords("en")) %>%
    textstat_keyness(target = 2)
textplot_wordcloud(tstat, max_words = 100)
textplot_wordcloud(tstat, comparison = FALSE, max_words = 100)