Study on feature selection and machine learning algorithms for Malay sentiment classification

Ahmed Alsaffar, Nazlia Omar

Research output: Chapter in Book/Report/Conference proceedingConference contribution

18 Citations (Scopus)

Abstract

Online social media is used to show the sentiments of different individuals about various subjects. Sentiment analysis or opinion mining has recently been considered as one of the highly dynamic research fields in natural language processing, web mining, and machine learning. There has been a very limited amount of research that focuses on sentiment analysis in the Malay language. This study investigates how feature selection methods contribute to the improvement of Malay sentiment classification performance. Three supervised machine-learning classifiers and seven feature selection methods are used to conduct a series of experiments for the effective selection of the appropriate methods for the automatic sentiment classification of online Malay-written reviews. Findings show that the classifications of Malay sentiment improve using feature selections approaches. This work demonstrates that all feature reduction methods generally improve classifier performance. Support Vector Machine (SVM) approach provide the highest accuracy performance of features selection in order to classify Malay sentiment comparing with other classifications approaches such as PCA and CHI square. SVM records 87% as experimental accuracy result of feature selection.

Original languageEnglish
Title of host publicationConference Proceedings - 6th International Conference on Information Technology and Multimedia at UNITEN: Cultivating Creativity and Enabling Technology Through the Internet of Things, ICIMU 2014
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages270-275
Number of pages6
ISBN (Print)9781479954230
DOIs
Publication statusPublished - 23 Mar 2015
Event6th International Conference on Information Technology and Multimedia, ICIMU 2014 - Putrajaya, Malaysia
Duration: 18 Nov 201420 Nov 2014

Other

Other6th International Conference on Information Technology and Multimedia, ICIMU 2014
CountryMalaysia
CityPutrajaya
Period18/11/1420/11/14

Fingerprint

Learning algorithms
Learning systems
Feature extraction
Support vector machines
Classifiers
Processing
Experiments

Keywords

  • Classifications
  • Feature Selection
  • Machine Learning
  • NLP
  • Sentiment analysis

ASJC Scopus subject areas

  • Computer Networks and Communications
  • Computer Science Applications
  • Information Systems
  • Software

Cite this

Alsaffar, A., & Omar, N. (2015). Study on feature selection and machine learning algorithms for Malay sentiment classification. In Conference Proceedings - 6th International Conference on Information Technology and Multimedia at UNITEN: Cultivating Creativity and Enabling Technology Through the Internet of Things, ICIMU 2014 (pp. 270-275). [7066643] Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/ICIMU.2014.7066643

Study on feature selection and machine learning algorithms for Malay sentiment classification. / Alsaffar, Ahmed; Omar, Nazlia.

Conference Proceedings - 6th International Conference on Information Technology and Multimedia at UNITEN: Cultivating Creativity and Enabling Technology Through the Internet of Things, ICIMU 2014. Institute of Electrical and Electronics Engineers Inc., 2015. p. 270-275 7066643.

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Alsaffar, A & Omar, N 2015, Study on feature selection and machine learning algorithms for Malay sentiment classification. in Conference Proceedings - 6th International Conference on Information Technology and Multimedia at UNITEN: Cultivating Creativity and Enabling Technology Through the Internet of Things, ICIMU 2014., 7066643, Institute of Electrical and Electronics Engineers Inc., pp. 270-275, 6th International Conference on Information Technology and Multimedia, ICIMU 2014, Putrajaya, Malaysia, 18/11/14. https://doi.org/10.1109/ICIMU.2014.7066643
Alsaffar A, Omar N. Study on feature selection and machine learning algorithms for Malay sentiment classification. In Conference Proceedings - 6th International Conference on Information Technology and Multimedia at UNITEN: Cultivating Creativity and Enabling Technology Through the Internet of Things, ICIMU 2014. Institute of Electrical and Electronics Engineers Inc. 2015. p. 270-275. 7066643 https://doi.org/10.1109/ICIMU.2014.7066643
Alsaffar, Ahmed ; Omar, Nazlia. / Study on feature selection and machine learning algorithms for Malay sentiment classification. Conference Proceedings - 6th International Conference on Information Technology and Multimedia at UNITEN: Cultivating Creativity and Enabling Technology Through the Internet of Things, ICIMU 2014. Institute of Electrical and Electronics Engineers Inc., 2015. pp. 270-275
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