A review of sentiment analysis research in Arabic language
This is an incremental review paper that addresses the gap in sentiment analysis research for Arabic, a language with high internet usage but underrepresented in NLP studies.
The paper reviews existing research on sentiment analysis for the Arabic language, highlighting that while it is a widely used language online, studies in this area are limited, and it analyzes the strengths and weaknesses of current approaches, including those using machine translation or transfer learning from English and those developed specifically for Arabic.
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.