The scripts process a data set consisting of tweets and their sentiment. It the filters the tweets by picking out words from the positive and negative dictionaries and creates a counter for each word. At the end of the script, we have a list of words with the count of the number of times they were used in a positive sense and a negative sense. This can now be used for Bayes Classification as the probability of a word appearing in a positive and negative scenario is known.