Sparse matrices
During the video lesson you learned about sparse matrices. Sparse matrices can become computational nightmares as the number of text documents and the number of unique words grow. Creating word representations with tweets can easily create sparse matrices because emojis, slang, acronyms, and other forms of language are used.
In this exercise you will walk through the steps to calculate how sparse the Russian tweet dataset is. Note that this is a small example of how quickly text analysis can become a major computational problem.
This exercise is part of the course
Introduction to Natural Language Processing in R
Hands-on interactive exercise
Have a go at this exercise by completing this sample code.
# Tokenize and remove stop words
tidy_tweets <- russian_tweets %>%
___(word, content) %>%
___(stop_words)
# Count by word
unique_words <- tidy_tweets %>%
count(___)