A Review on Challenging Issues in Arabic Sentiment Analysis

Ali Hamdi,Khaled Shaban,Anazida Zainal

doi:10.3844/jcssp.2016.471.481

Abstract

Understanding what people think about an idea or how they evaluate a product, a service or a policy is important for individuals, companies and governments. Sentiment analysis is the process of automatically identifying opinions expressed in text on certain subjects. The accuracy of sentiment analysis has a direct effect on decision making in both business and government. Working with the Arabic language is very important because of the growing number of online contents in Arabic and the existing resources are limited and the accuracy of existing methods is low. In this study, we do a survey to highlight Arabic sentiment analysis challenging issues based on two main perspectives: Arabic-specific and general linguistic issues. The Arabic-specific challenges are mainly caused by Arabic morphological complexity, limited resources and dialects, while the general linguistic issues include polarity fuzziness, polarity strength, implicit sentiment, sarcasm, spam, review quality and domain dependence.

Highlights

The use of microblogging services has led to wide spread availability of opinionated posts (El-Beltagy and Ali, 2013)
Using the different dialects in social media, where Arab users freely express themselves, adds more challenging to SA because the majority of the Natural Language Processing (NLP) tools for the Arabic language have been developed for modern standard Arabic (MSA)
Sentiment analysis have been used in various applications in public and customer opinion studies such as social, news and commerce domains

Summary

Introduction

The use of microblogging services has led to wide spread availability of opinionated posts (El-Beltagy and Ali, 2013). While some of them highlight the SA challenging issues, differently and albeit more comprehensively, the current manuscript attempts to cover such issues, discuss their causes to the SA low accuracy problem, focus on the Arabic language and highlight how previous work dealt with those issues. The language considered in this study, introduces additional difficulties when developing SA systems because of its morphological complexity, the existence of a large number of dialectal variants and the lack of resources.

Results

Conclusion