Arabic Sentiment Analysis: A Systematic Literature Review

Joint Authors

Mohsen, Abdulqader M.
Ghallab, Abdullatif
Ali, Yousef

Source

Applied Computational Intelligence and Soft Computing

Issue

Vol. 2020, Issue 2020 (31 Dec. 2020), pp.1-21, 21 p.

Publisher

Hindawi Publishing Corporation

Publication Date

2020-01-29

Country of Publication

Egypt

No. of Pages

21

Main Subjects

Information Technology and Computer Science

Abstract EN

With the recently grown attention from different research communities for opinion mining, there is an evolving body of work on Arabic Sentiment Analysis (ASA).

This paper introduces a systematic review of the existing literature relevant to ASA.

The main goals of the review are to support research, to propose further areas for future studies in ASA, and to smoothen the progress of other researchers’ search for related studies.

The findings of the review propose a taxonomy for sentiment classification methods.

Furthermore, the limitations of existing approaches are highlighted in the preprocessing step, feature generation, and sentiment classification methods.

Some likely trends for future research with ASA are suggested in both practical and theoretical aspects.

American Psychological Association (APA)

Ghallab, Abdullatif& Mohsen, Abdulqader M.& Ali, Yousef. 2020. Arabic Sentiment Analysis: A Systematic Literature Review. Applied Computational Intelligence and Soft Computing،Vol. 2020, no. 2020, pp.1-21.
https://search.emarefa.net/detail/BIM-1126023

Modern Language Association (MLA)

Ghallab, Abdullatif…[et al.]. Arabic Sentiment Analysis: A Systematic Literature Review. Applied Computational Intelligence and Soft Computing No. 2020 (2020), pp.1-21.
https://search.emarefa.net/detail/BIM-1126023

American Medical Association (AMA)

Ghallab, Abdullatif& Mohsen, Abdulqader M.& Ali, Yousef. Arabic Sentiment Analysis: A Systematic Literature Review. Applied Computational Intelligence and Soft Computing. 2020. Vol. 2020, no. 2020, pp.1-21.
https://search.emarefa.net/detail/BIM-1126023

Data Type

Journal Articles

Language

English

Notes

Includes bibliographical references

Record ID

BIM-1126023