As social media websites dominates our online landscape data from these sites is becoming increasingly important in many fields. In this project a machine learning model known as a Support Vector Machine is used to classify and predict emotional content within short social media posts known as Tweets. Due to SVM's limitation as a binary classifier two methods of multi-classification, One Versus All and One Versus One, are examined and the latter of the two is used to produce experimental statistics on two data sets.