Now we create a word cloud to highlight the most representative words within the negative and positive sentiments, for each book:

The Dhammapada:

filtered_books_words %>%
  filter(book == "Dhammapada") %>%
  inner_join(bing, by = "word") %>%
  count(word, sentiment, sort = TRUE) %>%
  acast(word ~ sentiment, value.var = "n", fill = 0) %>%
  comparison.cloud(colors = c("#cf0a00","#1a954d"),
                   random.order = FALSE,
                   rot.per = 0,
                   max.words = 50)

The Book of Mormon:

filtered_books_words %>%
  filter(book == "The Book of Mormon") %>%
  inner_join(bing, by = "word") %>%
  count(word, sentiment, sort = TRUE) %>%
  acast(word ~ sentiment, value.var = "n", fill = 0) %>%
  comparison.cloud(colors = c("#cf0a00","#1a954d"),
                   random.order = FALSE,
                   rot.per = 0,
                   max.words = 50)