Beta
118803

Sentiment Analysis for Arabic Social Media

Article

Last updated: 24 Dec 2024

Subjects

-

Tags

-

Abstract

With the spread of social media services in Arabic societies, it leads to the explosive growth of Arabic posts, or comments. These services generate a huge volume of opinionated data on different topics such as politics and businesses. Analyzing valuable subjective information from data would assist in a better understanding and making decisions. Therefore, sentiment analysis coincides with social media networks and has become the most interesting research field in the sentiment analysis process. However, there are several challenges faced the sentiment analysis process. Arabic Sentiment analysis is indeed in its infantile stage and it has not obtained thoroughly attention wherein several challenges still need to address. Some of these challenges result from the complexity of Arabic natural language and other challenges result from social media platform itself. In this manuscript, we first study the impact of social media challenges on the challenges of Arabic language. Our findings show that such challenges add more complexities to the sentiment analysis process. Based on these findings, we review the contributed proposals, which give rise on analyzing Arabic social media data. Our review methodology is based on a set of criteria, which we propose to assess the advantages and limitations of these proposals. The interesting point here is to help researchers identify the social sentiment analysis problems along with a comprehensive survey on the sentiment analysis levels and classification approaches. Finally, we compare these proposals in terms of the average accuracy and suggest a new hybrid approach based on our findings.

DOI

10.21608/ijci.2020.16170.1004

Keywords

Arabic social media, Aspect level, Sentiment Analysis, Twitter sentiment analysis

Authors

First Name

manal

Last Name

zayed

MiddleName

-

Affiliation

the Faculty of Computers and Information, Department of Computer Science, Menoufia University

Email

manal.esam@ci.menofia.edu.eg

City

-

Orcid

-

First Name

hamdi

Last Name

mousa

MiddleName

-

Affiliation

faculty of computers and information

Email

hamdy.mousa@ci.menfia.edu.eg

City

-

Orcid

-

First Name

Mohamed

Last Name

Elmenshawy

MiddleName

-

Affiliation

Faculty of Computers and Information

Email

mohamed.elmenshawy@ci.menofia.edu.eg

City

-

Orcid

-

Volume

7

Article Issue

1

Related Issue

17861

Issue Date

2020-10-01

Receive Date

2019-09-22

Publish Date

2020-10-15

Page Start

14

Page End

31

Print ISSN

1687-7853

Online ISSN

2735-3257

Link

https://ijci.journals.ekb.eg/article_118803.html

Detail API

https://ijci.journals.ekb.eg/service?article_code=118803

Order

2

Type

Original Article

Type Code

877

Publication Type

Journal

Publication Title

IJCI. International Journal of Computers and Information

Publication Link

https://ijci.journals.ekb.eg/

MainTitle

Sentiment Analysis for Arabic Social Media

Details

Type

Article

Created At

22 Jan 2023