Mariam Biltawi, Wael Etaiwi, Sara Tedmori, Amjad Hudaib, and Arafat Awajan, "Sentiment classification techniques for Arabic language: A survey," Information and Communication Systems (ICICS), 2016 7th International Conference on. IEEE, 2016.


With the advent of online data, sentiment analysis has received growing attention in recent years. Sentiment analysis aims to determine the overall sentiment orientation of a speaker or writer towards a specific entity or towards a specific feature of a specific entity. A fundamental task of sentiment analysis is sentiment classification, which aims to automatically classify opinionated text as being positive, negative, or neutral. Although the literature on sentiment classification is quite extensive, only a few endeavors to classify opinionated text written in the Arabic language can be found. This paper provides a comprehensive survey of existing lexicon, machine learning, and hybrid sentiment classification techniques for Arabic language.