Common text mining visuals

Text Mining with Bag-of-Words in R

Ted Kwartler

Instructor

Why make visuals?

Good visuals lead to quick conclusions
The brain efficiently processes visual information

Setting the scene

Term frequency plots with tm

# Convert TDM to matrix
coffee_m <- as.matrix(coffee_tdm)

# Sum rows and sort by frequency
term_frequency <- rowSums(coffee_m)
term_frequency <- sort(term_frequency,
                       decreasing = TRUE)

# Create a barplot
barplot(term_frequency[1:10],
        col = "tan",
        las = 2)

Term frequency plots with qdap

# Load qdap package
library(qdap)

# Find term frequencies
frequency <- freq_terms(
    tweets$text,
    top = 10,
    at.least = 3, 
    stopwords = "Top200Words"
  )

# Plot term frequencies
plot(frequency)

Let's practice!

Text Mining with Bag-of-Words in R