Arabic Sentiment Analysis using Supervised Classification

Sentiment analysis is a process during which the polarity (i.e. positive, negative or neutral) of a given text is determined. In general there are two approaches to address this problem; namely, machine learning approach or lexicon based approach. The current paper deals with sentiment analysis in Arabic reviews from a machine learning perspective. Three classifiers were applied on an in-house developed dataset of tweets/comments. In particular, the Naive Bayes, SVM and K-Nearest Neighbor classifiers were run on this dataset. The results show that SVM gives the highest precision while KNN (K=10) gives the highest Recall.