So far, our hope was that simply using the words independent of each other with the bag-of-words approach would suffice. Just from our intuition, however, we know that neutral tweets probably contain a higher fraction of nouns, while positive or negative tweets are more colorful, requiring more adjectives and verbs. What if we use this linguistic information of the tweets as well? If we could find out how many words in a tweet were nouns, verbs, adjectives, and so on, the classifier could probably take that into account too.