textplot_wordcloud: Plot features as a wordcloud

In quanteda.textplots: Plots for the Quantitative Analysis of Textual Data

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.

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(s)

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)
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"))

## Not run: 
# 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)

## End(Not run)

quanteda.textplots documentation built on April 6, 2023, 1:12 a.m.