With all of the tweets circulating every second it is hard to tell whether the sentiment behind a specific tweet will impact a company, or a person's, brand for being viral (positive), or devastate profit because it strikes a negative tone. Capturing sentiment in language is important in these times where decisions and reactions are created and updated in seconds. The rise of social media such as blogs and social networks has fueled interest in sentiment analysis.
This project applies LSTMs to classify sentiments.