The Science and Information (SAI) Organization
  • Home
  • About Us
  • Journals
  • Conferences
  • Contact Us

Publication Links

  • IJACSA
  • Author Guidelines
  • Publication Policies
  • Digital Archiving Policy
  • Promote your Publication
  • Metadata Harvesting (OAI2)

IJACSA

  • About the Journal
  • Call for Papers
  • Editorial Board
  • Author Guidelines
  • Submit your Paper
  • Current Issue
  • Archives
  • Indexing
  • Fees/ APC
  • Reviewers
  • Apply as a Reviewer

IJARAI

  • About the Journal
  • Archives
  • Indexing & Archiving

Special Issues

  • Home
  • Archives
  • Proposals
  • Guest Editors
  • SUSAI-EE 2025
  • ICONS-BA 2025
  • IoT-BLOCK 2025

Future of Information and Communication Conference (FICC)

  • Home
  • Call for Papers
  • Submit your Paper/Poster
  • Register
  • Venue
  • Contact

Computing Conference

  • Home
  • Call for Papers
  • Submit your Paper/Poster
  • Register
  • Venue
  • Contact

Intelligent Systems Conference (IntelliSys)

  • Home
  • Call for Papers
  • Submit your Paper/Poster
  • Register
  • Venue
  • Contact

Future Technologies Conference (FTC)

  • Home
  • Call for Papers
  • Submit your Paper/Poster
  • Register
  • Venue
  • Contact
  • Home
  • Call for Papers
  • Editorial Board
  • Guidelines
  • Submit
  • Current Issue
  • Archives
  • Indexing
  • Fees
  • Reviewers
  • Subscribe

DOI: 10.14569/IJACSA.2022.0130849
PDF

A Novel Hybrid Sentiment Analysis Classification Approach for Mobile Applications Arabic Slang Reviews

Author 1: Rabab Emad Saudy
Author 2: Alaa El Din M. El-Ghazaly
Author 3: Eman S. Nasr
Author 4: Mervat H. Gheith

International Journal of Advanced Computer Science and Applications(IJACSA), Volume 13 Issue 8, 2022.

  • Abstract and Keywords
  • How to Cite this Article
  • {} BibTeX Source

Abstract: Arabic language incurs from the shortage of accessible huge datasets for Sentiment Analysis (SA), Machine Learning (ML), and Deep Learning (DL) applications. In this paper, we present MASR, a simple Mobile Applications Arabic Slang Reviews dataset for SA, ML, and DL applications which comprises of 2469 Egyptian Mobile Apps reviews, and help app developers meet user requirements evolution. Our methodology consists of six phases. We collect mobile apps reviews dataset, then apply preprocessing steps, in addition perform SA tasks. To evaluate MASR datasets, first we apply ML classification techniques: K-Nearest Neighbors (K-NN), Support vector machine (SVM), Logistic Regression (LR), and Random Forest (RF), and DL classification technique: Multi-layer Perceptron Neural Network (MLP-NN). From the examination for pervious classification techniques, we adopted a hybrid classification approach combined from the top two ML classifier accuracy results (LR, RF), and DL classifier (MLP-NN). The findings prove the adequacy of a hybrid supervised classification approach for MASR datasets.

Keywords: Arabic sentiment analysis; mobile application; hybrid classification model; hybrid supervised classification approach; Google play store; random forest; logistic regression; neural network; multi-layer perceptron neural network; machine learning; deep learning

Rabab Emad Saudy, Alaa El Din M. El-Ghazaly, Eman S. Nasr and Mervat H. Gheith, “A Novel Hybrid Sentiment Analysis Classification Approach for Mobile Applications Arabic Slang Reviews” International Journal of Advanced Computer Science and Applications(IJACSA), 13(8), 2022. http://dx.doi.org/10.14569/IJACSA.2022.0130849

@article{Saudy2022,
title = {A Novel Hybrid Sentiment Analysis Classification Approach for Mobile Applications Arabic Slang Reviews},
journal = {International Journal of Advanced Computer Science and Applications},
doi = {10.14569/IJACSA.2022.0130849},
url = {http://dx.doi.org/10.14569/IJACSA.2022.0130849},
year = {2022},
publisher = {The Science and Information Organization},
volume = {13},
number = {8},
author = {Rabab Emad Saudy and Alaa El Din M. El-Ghazaly and Eman S. Nasr and Mervat H. Gheith}
}



Copyright Statement: This is an open access article licensed under a Creative Commons Attribution 4.0 International License, which permits unrestricted use, distribution, and reproduction in any medium, even commercially as long as the original work is properly cited.

IJACSA

Upcoming Conferences

IntelliSys 2025

28-29 August 2025

  • Amsterdam, The Netherlands

Future Technologies Conference 2025

6-7 November 2025

  • Munich, Germany

Healthcare Conference 2026

21-22 May 2026

  • Amsterdam, The Netherlands

Computing Conference 2026

9-10 July 2026

  • London, United Kingdom

IntelliSys 2026

3-4 September 2026

  • Amsterdam, The Netherlands

Computer Vision Conference 2026

15-16 October 2026

  • Berlin, Germany
The Science and Information (SAI) Organization
BACK TO TOP

Computer Science Journal

  • About the Journal
  • Call for Papers
  • Submit Paper
  • Indexing

Our Conferences

  • Computing Conference
  • Intelligent Systems Conference
  • Future Technologies Conference
  • Communication Conference

Help & Support

  • Contact Us
  • About Us
  • Terms and Conditions
  • Privacy Policy

© The Science and Information (SAI) Organization Limited. All rights reserved. Registered in England and Wales. Company Number 8933205. thesai.org