Plot a dfm 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.

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)



a dfm object


size of the smallest word


size of the largest word


words with frequency below min_count will not be plotted


maximum number of words to be plotted. least frequent terms dropped.


color of words from least to most frequent


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


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


proportion of words with 90 degree rotation


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


choose colors randomly from the colors. If FALSE, the color is chosen based on the frequency


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


color of group labels. Only used when compariosn=TRUE.


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


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


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


if TRUE, plot a wordclound that compares documents in the same way as


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.


# plot the features (without stopwords) from Obama's inaugural addresses set.seed(10) obama_dfm <- dfm(corpus_subset(data_corpus_inaugural, President == "Obama"), remove = stopwords("english"), remove_punct = TRUE) %>% dfm_trim(min_termfreq = 3) # basic wordcloud textplot_wordcloud(obama_dfm)
# plot in colors with some additional options textplot_wordcloud(obama_dfm, 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(obama_dfm, adjust = 0.5, random_order = FALSE, color = col, rotation = FALSE)
# comparison plot of Obama v. Trump obama_trump_dfm <- 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(obama_trump_dfm, comparison = TRUE, max_words = 300, color = c("blue", "red"))