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

Publication Links

  • IJACSA
  • Author Guidelines
  • Publication Policies
  • Outstanding Reviewers

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
  • ICONS_BA 2025

Computer Vision Conference (CVC)

  • 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
  • RSS Feed

DOI: 10.14569/IJACSA.2024.0150945
PDF

Subjectivity Analysis of an Enhanced Feature Set for Code-Switching Text

Author 1: Emaliana Kasmuri
Author 2: Halizah Basiron

International Journal of Advanced Computer Science and Applications(IJACSA), Volume 15 Issue 9, 2024.

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

Abstract: The phenomenon of code-switching has posed a new challenge to the linguistic computing area. Conventionally, the computer will process monolingual text or multilingual text. However, code-switching is different from this kind of text. Two or more languages are used to construct a piece of code-switching text, particularly a code-switching sentence. It is challenging for the computer to process a piece of code-switching text with languages that exist simultaneously. The challenge is more intense for the computer in subjectivity analysis, where the computer should distinguish subjective from objective code-switching text. This paper proposed three feature sets for subjectivity analysis on Malay-English code-switching text: Embedded Code-Switching Feature Sets, Unified Code-Switching Feature Sets, and Stylistic Feature Sets. These feature sets were enhanced from the monolingual feature set of subjectivity analysis. Experiments were conducted using the data harvested from Malay-English blogs. These data were labelled as either subjective or objective. Two machine learning classifiers – the Support Vector Machine (SVM) and Naive-Bayes, were used to evaluate the classification performance of the proposed feature sets. The experiments were carried out on individual feature sets and the combination of them. The results show the classification performance from combining the unified and stylistic feature sets surpassed other proposed feature sets at 59% accuracy. Therefore, it is concluded that the combination of unified and stylistic feature sets is necessary for the subjectivity analysis of Malay-English code-switching text.

Keywords: Subjectivity analysis; code-switching; enhanced feature sets; Malay-English text

Emaliana Kasmuri and Halizah Basiron. “Subjectivity Analysis of an Enhanced Feature Set for Code-Switching Text”. International Journal of Advanced Computer Science and Applications (IJACSA) 15.9 (2024). http://dx.doi.org/10.14569/IJACSA.2024.0150945

@article{Kasmuri2024,
title = {Subjectivity Analysis of an Enhanced Feature Set for Code-Switching Text},
journal = {International Journal of Advanced Computer Science and Applications},
doi = {10.14569/IJACSA.2024.0150945},
url = {http://dx.doi.org/10.14569/IJACSA.2024.0150945},
year = {2024},
publisher = {The Science and Information Organization},
volume = {15},
number = {9},
author = {Emaliana Kasmuri and Halizah Basiron}
}



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

Computer Vision Conference (CVC) 2026

21-22 May 2026

  • Amsterdam, The Netherlands

Computing Conference 2026

9-10 July 2026

  • London, United Kingdom

Artificial Intelligence Conference 2026

3-4 September 2026

  • Amsterdam, The Netherlands

Future Technologies Conference (FTC) 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

  • Computer Vision Conference
  • Computing Conference
  • Intelligent Systems Conference
  • Future Technologies Conference

Help & Support

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

The Science and Information (SAI) Organization Limited is a company registered in England and Wales under Company Number 8933205.