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Visualize word networks

Another way to view word connections is to treat them as a network, similar to a social network. Word networks show term association and cohesion. A word of caution: these visuals can become very dense and hard to interpret visually.

In a network graph, the circles are called nodes and represent individual terms, while the lines connecting the circles are called edges and represent the connections between the terms.

For the over-caffeinated text miner, qdap provides a shortcut for making word networks. The word_network_plot() and word_associate() functions both make word networks easy!

The sample code constructs a word network for words associated with "Marvin".

This exercise is part of the course

Text Mining with Bag-of-Words in R

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Exercise instructions

Update the word_associate() plotting code to work with the coffee data.

  • Change the vector to coffee_tweets$text.
  • Change the match string to "barista".
  • Change "chardonnay" to "coffee" in the stopwords too.
  • Change the title to "Barista Coffee Tweet Associations" in the sample code for the plot.

Hands-on interactive exercise

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

# Word association
word_associate(chardonnay_tweets$text, match.string = "marvin", 
               stopwords = c(Top200Words, "chardonnay", "amp"), 
               network.plot = TRUE, cloud.colors = c("gray85", "darkred"))

# Add title
title(main = "Chardonnay Tweets Associated with Marvin")
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