Review Article Open Access

A Review on Challenging Issues in Arabic Sentiment Analysis

Ali Hamdi1, Khaled Shaban2 and Anazida Zainal1
  • 1 Universiti Teknologi Malaysia, Malaysia
  • 2 Qatar University, Qatar

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.

Journal of Computer Science
Volume 12 No. 9, 2016, 471-481

DOI: https://doi.org/10.3844/jcssp.2016.471.481

Submitted On: 7 September 2016 Published On: 11 December 2016

How to Cite: Hamdi, A., Shaban, K. & Zainal, A. (2016). A Review on Challenging Issues in Arabic Sentiment Analysis. Journal of Computer Science, 12(9), 471-481. https://doi.org/10.3844/jcssp.2016.471.481

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Keywords

  • Sentiment Analysis
  • Opinion Mining
  • Computational Linguistics
  • Text Classification