Sentiment Analysis for Arabic text using Deep Learning Techniques

Abstract

Sentiment analysis is the research field that examines people's language for their views, feelings, assessments, attitudes, and emotions. The growing importance of sentiment analysis corresponds to social media platforms such as reviews, blogs, microblogs, forum discussions, Twitter, and social networks. These platforms have a huge amount of data on them. This massive volume of data necessitates quick and precise analysis techniques, which aid decision-making in various disciplines and changes policy as needed. Emotion analysis is one of the most common sentiment analysis jobs, aiming to observe and distinguish different sorts of sentiments/emotions expressed through language expression. The research interest in Arabic sentiment analysis has increased drastically due to the internet's vast number of Arabic language users. This work built a framework for multilabel emotion analysis from Arabic tweets. The Arabic tweets dataset used has been provided by SemEval 2018-Task1, E-c subtask.