Kernel density plot

Now that you learned about a kernel density plot you can create one! Remember it's like a smoothed histogram but isn't affected by binwidth. This exercise will help you construct a kernel density plot from sentiment values.

In this exercise you will plot 2 kernel densities. One for Agamemnon and another for The Wizard of Oz. For both you will perform an inner_join() with the "afinn" lexicon. Recall the "afinn" lexicon has terms scored from -5 to 5. Once in a tidy format, both books will retain words and corresponding scores for the lexicon.

After that, you need to row bind the results into a larger data frame using bind_rows() and create a plot with ggplot2.

From the visual you will be able to understand which book uses more positive versus negative language. There is clearly overlap as negative things happen to Dorothy but you could infer the kernel density is demonstrating a greater probability of positive language in the Wizard of Oz compared to Agamemnon.

We've loaded ag and oz as tidy versions of Agamemnon and The Wizard of Oz respectively, and created afinn as a subset of the tidytext "afinn" lexicon.

This exercise is part of the course

Sentiment Analysis in R

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Hands-on interactive exercise

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

ag_afinn <- ag %>% 
  # Inner join to afinn lexicon
  ___(___, by = c("term" = "word"))

oz_afinn <- oz %>% 
  # Inner join to afinn lexicon
  ___ 

# Combine
all_df <- ___(agamemnon = ___, oz = ___, .id = "___")

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