Generally, the performance of sentiment classification is evaluated by using four indexes, namely: Accuracy, Precision, Recall and F1-score. Accuracy is the proportion of all true predicted instances against all predicted instances. An accuracy of 100% means that the predicted instances are exactly the same as the actual instances. Precision refers to the portion of true predicted instances against all predicted instances for each class. Recall denotes the portion of true predicted instances against all actual instances for each class. F1 is a harmonic average of precision and recall.