A review of sentiment analysis research in Arabic language

TL;DR

This paper reviews the current state of sentiment analysis research in Arabic, highlighting the challenges, approaches, and progress made in adapting techniques to the Arabic language.

Contribution

It provides a comprehensive qualitative survey of Arabic sentiment analysis methods, including translation-based and native approaches, identifying strengths and limitations.

Findings

Limited Arabic sentiment datasets available

Transfer learning shows promising results for Arabic

Native Arabic approaches face unique linguistic challenges

Abstract

Sentiment analysis is a task of natural language processing which has recently attracted increasing attention. However, sentiment analysis research has mainly been carried out for the English language. Although Arabic is ramping up as one of the most used languages on the Internet, only a few studies have focused on Arabic sentiment analysis so far. In this paper, we carry out an in-depth qualitative study of the most important research works in this context by presenting limits and strengths of existing approaches. In particular, we survey both approaches that leverage machine translation or transfer learning to adapt English resources to Arabic and approaches that stem directly from the Arabic language.