Details

Autor(en) / Beteiligte

• Abo, Mohamed Elhag Mohamed
• Raj, Ram Gopal
• Qazi, Atika

Titel

A Review on Arabic Sentiment Analysis: State-of-the-Art, Taxonomy and Open Research Challenges

Ist Teil von

• IEEE access, 2019, Vol.7, p.162008-162024

Ort / Verlag

Piscataway: IEEE

Erscheinungsjahr

2019

Quelle

EZB Electronic Journals Library

Beschreibungen/Notizen

• 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.