Natural Language Processing for Arabic Sentiment Analysis: A Systematic Literature Review-Reference-Cited by-同舟云学术

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Natural Language Processing for Arabic Sentiment Analysis: A Systematic Literature Review

Published:2024-10 Issue:5 Volume:10 Page:576-594
ISSN:2332-7790
Container-title:IEEE Transactions on Big Data
language:
Short-container-title:IEEE Trans. Big Data

Author:

Al Katat Souha¹^ORCID,Zaki Chamseddine²^ORCID,Hazimeh Hussein³^ORCID,El Bitar Ibrahim⁴^ORCID,Angarita Rafael⁵^ORCID,Trojman Lionel¹^ORCID

Affiliation:

1. Institut Supérieur d’Electronique de Paris – Isep, Paris, France

2. College of Engineering and Technology, American University of the Middle East, Egaila, Kuwait

3. Faculty of Science and Al-PSPACEAU-Maaref University, MIDIL Lab, Lebanese University, Beirut, Lebanon

4. Lebanese University-Faculty of Sciences and Lebanese International University-School of Engineering, Beirut, Lebanon

5. LIP6, Sorbonne University and Nanterre University, Paris, France

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Link

http://xplorestaging.ieee.org/ielx7/6687317/10663875/10436333.pdf?arnumber=10436333

Reference129 articles.

1. Sentiment analysis of Emirati dialect;Shamsi;Big Data Cogn. Comput.,2022

2. Ensemble classifiers for Arabic sentiment analysis of social network (twitter data) towards COVID-19-related conspiracy theories;Abdullah;Appl. Comput. Intell. Soft Comput.,2022

3. AraXLNet: pre-trained language model for sentiment analysis of Arabic

4. Arabic Sentiment Analysis Using Deep Learning and Ensemble Methods

5. AraSenCorpus: A Semi-Supervised Approach for Sentiment Annotation of a Large Arabic Text Corpus

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