Arabic Sentiment Analysis: A Systematic Literature Review. (29th January 2020)

• Record Type: Journal Article
• Authors: Ghallab, Abdullatif; Mohsen, Abdulqader; Ali, Yousef
• Other Names: Dawson Christian W. Academic Editor.
• Is Part Of: Applied computational intelligence and soft computing. Volume 2020(2020)
• Publication Date: 2020-01-29
• Subjects: Computational intelligence -- Periodicals; Soft computing -- Periodicals; 006.305
• DOI: 10.1155/2020/7403128
• Languages: English
• ISSNs: 1687-9724

Abstract

Abstract : With the recently grown attention from different research communities for opinion mining, there is an evolving body of work on Arabic Sentiment Analysis (ASA). This paper introduces a systematic review of the existing literature relevant to ASA. The main goals of the review are to support research, to propose further areas for future studies in ASA, and to smoothen the progress of other researchers' search for related studies. The findings of the review propose a taxonomy for sentiment classification methods. Furthermore, the limitations of existing approaches are highlighted in the preprocessing step, feature generation, and sentiment classification methods. Some likely trends for future research with ASA are suggested in both practical and theoretical aspects.