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.2019.0100878
PDF

Arabic Lexicon Learning to Analyze Sentiment in Microblogs

Author 1: Mahmoud B Rokaya
Author 2: Ahmed S. Ghiduk
Author 3: Mahmoud B. Rokaya
Author 4: Ahmed S. Ghiduk

International Journal of Advanced Computer Science and Applications(IJACSA), Volume 10 Issue 8, 2019.

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

Abstract: The study and classifying of opinions distilled from social media is called sentiment analysis. The goal of this study is to build an adaptive sentiment lexicon for Arabic language. Based on those lexicons the sentiments polarity classification can be improved. The classification problem will be stated as a mathematical programming problem. In this problem, we search a lexicon that optimizes the classification accuracy. A genetic algorithm is presented to solve the optimization problem. A meta-level feature is generated based on the adaptive lexicons provided by the genetic algorithm. The algorithm performance is supported by using it alongside n-gram features and Bing liu’s lexicon. In this work, lexicon-based and corpora-based approaches are integrated, and the lexicons are produced from the corpus. Five data sets are tested through experiments. The sentiments in all data sets are classified based on five polarity levels. A better understanding of words sentiment orientation, social media users’ culture and Arabic language can be achieved based on the lexicons generated by the proposed algorithm. Since stop words can contribute and add to the sentiment polarity, stop words will be considered and will not deleted. The results show that the F-measure is greater than 80 % in three data sets and the accuracy is greater than 80 % for all data sets. The proposed method out-performs the current methods in the literature in two of the datasets. Finally, in terms of F-measure, the proposed methods achieved better results for three datasets.

Keywords: Sentiment analysis; sentiment lexicon; social media; twitter; optimization; mathematical programming; genetic algorithm; evolutionary computation; arabic language

Mahmoud B Rokaya, Ahmed S. Ghiduk, Mahmoud B. Rokaya and Ahmed S. Ghiduk, “Arabic Lexicon Learning to Analyze Sentiment in Microblogs” International Journal of Advanced Computer Science and Applications(IJACSA), 10(8), 2019. http://dx.doi.org/10.14569/IJACSA.2019.0100878

@article{Rokaya2019,
title = {Arabic Lexicon Learning to Analyze Sentiment in Microblogs},
journal = {International Journal of Advanced Computer Science and Applications},
doi = {10.14569/IJACSA.2019.0100878},
url = {http://dx.doi.org/10.14569/IJACSA.2019.0100878},
year = {2019},
publisher = {The Science and Information Organization},
volume = {10},
number = {8},
author = {Mahmoud B Rokaya and Ahmed S. Ghiduk and Mahmoud B. Rokaya and Ahmed S. Ghiduk}
}



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