Retracted: Emotions classification for Arabic tweets

Abstract

Millions of sentiments, emotions, opinions and criticisms expressed on Twitter every day are beginning to be an important source of information for individuals, numerous companies and organizations. Knowing the perception about relevant products, services, events or personalities, as well as monitoring their online reputation are some of the objectives that the companies have marked in the short term. So the requirement of user emotions analysis and classification is gaining importance day by day. Most of studies focus on sentiments analysis as positive and negative but none of them go deeper to analysis and classify the emotions behind Tweets. Arabic language become a hard challenge for emotions classification on twitter and it involves more preprocessing before classification than other languages. This paper presents a model for extracting and classifying emotions in Arabic tweets based on four emotions sad, joy, disgust and anger.