Improving Sentiment Analysis of Arabic Tweets

Abstract

Twitter popularity grew rapidly the last years and become a place where people express their opinions, views, feelings and ideas. This popularity and the vast amount of information triggered the interest of companies as well as researchers on sentiment analysis trying to export meaningful results from this information. Even if there is a tremendous amount of work on Latin originated languages, such as English, there is not much research available on native languages such as Arabic, Greek etc. This research aims to develop a new system able to bridge the gap in Arabic users and sentiment analysis by providing a novel dictionary able to classify Arabic Tweets with different Arabic dialects and emotions, as positive, negative or natural. The study provides a quantitative analysis to gain an in-depth understanding of the phenomenon under investigation and the findings of the study show that the designed system is very promising.