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Sentiment and emotion

Within the sentiments dataset, the lexicon nrc contains a dictionary of words and an emotion associated with that word. Emotions such as joy, trust, anticipation, and others are found within this dataset.

In the Russian tweet bot dataset you have been exploring, you have looked at tweets sent out by both a left- and a right-leaning tweet bot. Explore the contents of the tweets sent by the left-leaning (democratic) tweet bot by using the nrc lexicon. The left tweets, left, have been tokenized into words, with stop-words removed.

This exercise is part of the course

Introduction to Natural Language Processing in R

View Course

Exercise instructions

  • Create a tibble of just the anticipation words from the nrc lexicon.
  • Create a tibble of just the joy words from the nrc lexicon.
  • Print the top anticipation words found in left_tokens.
  • Print the top joy words found in left_tokens.

Hands-on interactive exercise

Have a go at this exercise by completing this sample code.

left_tokens <- left %>%
  unnest_tokens(output = "word", token = "words", input = content) %>%
  anti_join(stop_words)
# Dictionaries 
anticipation <- ___("nrc") %>% 
  ___(sentiment == "anticipation")
joy <- ___("nrc") %>% 
  ___(sentiment == "joy")
# Print top words for Anticipation and Joy
left_tokens %>%
  ___(anticipation, by = "word") %>%
  ___(word, sort = TRUE)
left_tokens %>%
  ___(joy, by = "word") %>%
  ___(word, sort = TRUE)
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