This web app visually displays the general emotion and tone surrounding the two main party candidates in the 2016 election. It fetches and analyzes tweets using the Twitter REST API and classifies emotion and tone using IBM's Waston Developer Cloud. It displays this data in 3 graphs, a bar graph, a radar graph, and a word cloud. The bar graph shows the ratio of angry tweets from one candidate's supporters to the other candidate's supporters. The radar grapth shows 5 different social tendencies that each candidate's supporters demonstrate. Finally, the word cloud shows the frequency of words that each candidate supporter's uses.

Aside from using Twitter and Waston, we used Firebase for a database. The front end uses Javascript/HTML, and the backend uses Java.