Sentiment Analysis in Arabic Tweets

Abstract

Sentiment analysis is one of the most active research areas in natural language processing in recent years. It is the computational study of sentiments and emotions expressed in written human languages. While emotions are central to almost all human activities, especially in Social Media, social big data becomes one of the most important source of data for sentiment analysis. This work consists in developing a platform that presents our contribution in the field of classification of the polarity (Positive/Negative) by using machine learning techniques (classification model) and a generated database. This last is consisted of Twitter comments or “tweets” written in both Modern Standard Arabic (MSA) and Algerian Dialectal Arabic. For the favour of the sentiment analysis field, in our work we fortunately managed the use of Random Forest learning model.