In this thesis, the author examines the last 131 days of the 2016 election cycle. This analysis focuses on how sentiment is present on Twitter when people engage in political communication on social media. With the increasing online political discussions created on social media such as Twitter, an analysis of sentiment is critical. The data could be obtainable for candidates to estimate the electorate’s opinion of each candidate. A shift of sentiment offers a deeper insight into tracking changing attitudes toward candidates. Because Twitter only allows each tweet to be 140 characters there is a simplicity that offers statements to be concise. Trends for each candidate throughout the final days of the election cycle are correlated with national polls to assess if there is a relationship present. This study applies sentiment to recognize trends that may estimate a candidate’s chance of winning the election and offers indications as to how the intended electorate may vote when a relationship is established between sentiment and national polls.