research-article

Autoregressive Feature Extraction with Topic Modeling for Aspect-based Sentiment Analysis of Arabic as a Low-resource Language

Authors:

Asmaa Hashem Sweidan,

Nashwa El-Bendary,

Esraa ElhaririAuthors Info & Claims

ACM Transactions on Asian and Low-Resource Language Information Processing, Volume 23, Issue 2

Article No.: 23, Pages 1 - 18

https://doi.org/10.1145/3638050

Published: 08 February 2024 Publication History

Abstract

This paper proposes an approach for aspect-based sentiment analysis of Arabic social data, especially the considerable text corpus generated through communications on X (formerly known as Twitter) for expressing opinions in Arabic-language tweets during the COVID-19 pandemic. The proposed approach examines the performance of several pre-trained predictive and autoregressive language models; namely, Bidirectional Encoder Representations from Transformers (BERT) and XLNet, along with topic modeling algorithms; namely, Latent Dirichlet Allocation (LDA) and Non-negative Matrix Factorization (NMF), for aspect-based sentiment analysis of online Arabic text. In addition, Bidirectional Long Short Term Memory (Bi-LSTM) deep learning model is used to classify the extracted aspects from online reviews. Obtained experimental results indicate that the combined XLNet-NMF model outperforms other implemented state-of-the-art methods through improving the feature extraction of unstructured social media text with achieving values of 0.946 and 0.938, for average sentiment classification accuracy and F-measure, respectively.

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Cited By

Sweidan AEl-Bendary NTaie SIdrees AElhariri E(2025)Explainable Deep Learning for COVID-19 Vaccine Sentiment in Arabic Tweets Using Multi-Self-Attention BiLSTM with XLNetBig Data and Cognitive Computing10.3390/bdcc90200379:2(37)Online publication date: 10-Feb-2025
https://doi.org/10.3390/bdcc9020037
Berber TEriş Büyükkaya M(2025)Performance Comparison of Text Weighting Schemas on NMF-Based Topic AnalysisDokuz Eylül Üniversitesi Mühendislik Fakültesi Fen ve Mühendislik Dergisi10.21205/deufmd.202527790727:79(46-53)Online publication date: 23-Jan-2025
https://doi.org/10.21205/deufmd.2025277907
Santos POliveira LLima MSouza DSilva JOliveira GBrom PChahad ALopes CSilva MBatista K(2024)Exploring public-private partnerships in Latin America and the Caribbean using topic modeling and sentiment analysisCaderno Pedagógico10.54033/cadpedv21n9-02321:9(e7428)Online publication date: 4-Sep-2024
https://doi.org/10.54033/cadpedv21n9-023
Show More Cited By

Index Terms

Autoregressive Feature Extraction with Topic Modeling for Aspect-based Sentiment Analysis of Arabic as a Low-resource Language
1. Computing methodologies
  1. Artificial intelligence
    1. Natural language processing
      1. Information extraction

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Published In

cover image ACM Transactions on Asian and Low-Resource Language Information Processing

ACM Transactions on Asian and Low-Resource Language Information Processing Volume 23, Issue 2

February 2024

340 pages

EISSN:2375-4702

DOI:10.1145/3613556

Editor:
Imed Zitouni
Google, USA

Issue’s Table of Contents

Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than the author(s) must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected].

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Association for Computing Machinery

New York, NY, United States

Publication History

Published: 08 February 2024

Online AM: 27 December 2023

Accepted: 17 November 2023

Received: 07 September 2023

Published in TALLIP Volume 23, Issue 2

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Cited By

Sweidan AEl-Bendary NTaie SIdrees AElhariri E(2025)Explainable Deep Learning for COVID-19 Vaccine Sentiment in Arabic Tweets Using Multi-Self-Attention BiLSTM with XLNetBig Data and Cognitive Computing10.3390/bdcc90200379:2(37)Online publication date: 10-Feb-2025
https://doi.org/10.3390/bdcc9020037
Berber TEriş Büyükkaya M(2025)Performance Comparison of Text Weighting Schemas on NMF-Based Topic AnalysisDokuz Eylül Üniversitesi Mühendislik Fakültesi Fen ve Mühendislik Dergisi10.21205/deufmd.202527790727:79(46-53)Online publication date: 23-Jan-2025
https://doi.org/10.21205/deufmd.2025277907
Santos POliveira LLima MSouza DSilva JOliveira GBrom PChahad ALopes CSilva MBatista K(2024)Exploring public-private partnerships in Latin America and the Caribbean using topic modeling and sentiment analysisCaderno Pedagógico10.54033/cadpedv21n9-02321:9(e7428)Online publication date: 4-Sep-2024
https://doi.org/10.54033/cadpedv21n9-023
Al-Mutawa RAl-Aama A(2024)Arabic Opinion Classification of Customer Service Conversations Using Data Augmentation and Artificial IntelligenceBig Data and Cognitive Computing10.3390/bdcc81201968:12(196)Online publication date: 19-Dec-2024
https://doi.org/10.3390/bdcc8120196
Aladeemy AAlzahrani AAlgarni MAlsubari SAldhyani TDeshmukh SKhalaf OWong WAqburi S(2024)Advancements and challenges in Arabic sentiment analysis: A decade of methodologies, applications, and resource developmentHeliyon10.1016/j.heliyon.2024.e3978610:21(e39786)Online publication date: Nov-2024
https://doi.org/10.1016/j.heliyon.2024.e39786

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