عنوان المقالة:A Review on Arabic Sentiment Analysis: State-of-the-Art, Taxonomy and Open Research Challenges A review on Arabic sentiment analysis: state-of-the-art, taxonomy and open research challenges
د. محمد الحاج محمد أبو | Dr. Mohamed Elhag Mohamed Abo | 8696
نوع النشر
مجلة علمية
المؤلفون بالعربي
Mohamed Elhag Mohamed Abo, Ram Gopal Raj, Atika Qazi
المؤلفون بالإنجليزي
Mohamed Elhag Mohamed Abo, Ram Gopal Raj, Atika Qazi
الملخص العربي
Due to the significant use of Arabic language in social media networks, the demand for Arabic sentiment analysis has increased rapidly. Although, numerous sentiment analysis techniques enable people to obtain valuable insights from the opinions shared on social media. However, these techniques are still in their infancy, and the Arabic sentiment analysis domain lacks a compressive survey. Therefore, this study focused on the various characteristics, State-of-the-Art, and the level of sentiment analysis along with the natural language processing applied in the Arabic sentiment analysis. Furthermore, this study also discussed the sentiment analysis of the modern standards and the dialects of Arabic languages along with various machine learning processes and a few popular algorithms. Moreover, this study adds values by critical analysis of two case studies, which displayed an extensive set of the various research communities in this field of sentiment analysis. Finally, open research challenges are investigated, with a focus on the shortage of lexicons; availability; use of Dialect Arabic (DA); lack of corpora and datasets; right to left reading and compound phrases and idioms.
الملخص الانجليزي
Due to the significant use of Arabic language in social media networks, the demand for Arabic sentiment analysis has increased rapidly. Although, numerous sentiment analysis techniques enable people to obtain valuable insights from the opinions shared on social media. However, these techniques are still in their infancy, and the Arabic sentiment analysis domain lacks a compressive survey. Therefore, this study focused on the various characteristics, State-of-the-Art, and the level of sentiment analysis along with the natural language processing applied in the Arabic sentiment analysis. Furthermore, this study also discussed the sentiment analysis of the modern standards and the dialects of Arabic languages along with various machine learning processes and a few popular algorithms. Moreover, this study adds values by critical analysis of two case studies, which displayed an extensive set of the various research communities in this field of sentiment analysis. Finally, open research challenges are investigated, with a focus on the shortage of lexicons; availability; use of Dialect Arabic (DA); lack of corpora and datasets; right to left reading and compound phrases and idioms.
تاريخ النشر
11/04/2019
الناشر
IEEE Access
رقم المجلد
7
رقم العدد
7
ISSN/ISBN
2169-3536
رابط DOI
10.1109/ACCESS.2019.2951530
الصفحات
162024
رابط خارجي
https://ieeexplore.ieee.org/abstract/document/8890900
الكلمات المفتاحية
Sentiment analysis , Social networking (online) , Machine learning , Machine learning algorithms , Supervised learning , Standards , Classification algorithms
رجوع