Metaheuristic algorithms for feature selection in sentiment analysis

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

16 Citations (Scopus)

Abstract

Sentiment analysis functions by analyzing and extracting opinions from documents, websites, blogs, discussion forums and others to identify sentiment patterns on opinions expressed by consumers. It analyzes people's sentiment and identifies types of sentiment in comments expressed by consumers on certain matters. This paper highlights comparative studies on the types of feature selection in sentiment analysis based on natural language processing and modern methods such as Genetic Algorithm and Rough Set Theory. This study compares feature selection in text classification based on traditional and sentiment analysis methods. Feature selection is an important step in sentiment analysis because a suitable feature selection can identify the actual product features criticized or discussed by consumers. It can be concluded that metaheuristic based algorithms have the potential to be implemented in sentiment analysis research and can produce an optimal subset of features by eliminating features that are irrelevant and redundant.

Original languageEnglish
Title of host publicationProceedings of the 2015 Science and Information Conference, SAI 2015
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages222-226
Number of pages5
ISBN (Print)9781479985470
DOIs
Publication statusPublished - 2 Sep 2015
EventScience and Information Conference, SAI 2015 - London, United Kingdom
Duration: 28 Jul 201530 Jul 2015

Other

OtherScience and Information Conference, SAI 2015
CountryUnited Kingdom
CityLondon
Period28/7/1530/7/15

Fingerprint

Feature extraction
Blogging
Natural Language Processing
Rough set theory
Blogs
Research
set theory
Websites
weblog
Genetic algorithms
website
Processing
language

Keywords

  • feature selection
  • metaheuristic algorithms
  • opinion mining
  • sentiment analysis

ASJC Scopus subject areas

  • Health Informatics
  • Social Sciences (miscellaneous)
  • Computer Science Applications
  • Human-Computer Interaction
  • Computer Networks and Communications
  • Information Systems
  • Software

Cite this

Ahmad, S. R., Abu Bakar, A., & Yaakub, M. R. (2015). Metaheuristic algorithms for feature selection in sentiment analysis. In Proceedings of the 2015 Science and Information Conference, SAI 2015 (pp. 222-226). [7237148] Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/SAI.2015.7237148

Metaheuristic algorithms for feature selection in sentiment analysis. / Ahmad, Siti Rohaidah; Abu Bakar, Azuraliza; Yaakub, Mohd Ridzwan.

Proceedings of the 2015 Science and Information Conference, SAI 2015. Institute of Electrical and Electronics Engineers Inc., 2015. p. 222-226 7237148.

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

Ahmad, SR, Abu Bakar, A & Yaakub, MR 2015, Metaheuristic algorithms for feature selection in sentiment analysis. in Proceedings of the 2015 Science and Information Conference, SAI 2015., 7237148, Institute of Electrical and Electronics Engineers Inc., pp. 222-226, Science and Information Conference, SAI 2015, London, United Kingdom, 28/7/15. https://doi.org/10.1109/SAI.2015.7237148
Ahmad SR, Abu Bakar A, Yaakub MR. Metaheuristic algorithms for feature selection in sentiment analysis. In Proceedings of the 2015 Science and Information Conference, SAI 2015. Institute of Electrical and Electronics Engineers Inc. 2015. p. 222-226. 7237148 https://doi.org/10.1109/SAI.2015.7237148
Ahmad, Siti Rohaidah ; Abu Bakar, Azuraliza ; Yaakub, Mohd Ridzwan. / Metaheuristic algorithms for feature selection in sentiment analysis. Proceedings of the 2015 Science and Information Conference, SAI 2015. Institute of Electrical and Electronics Engineers Inc., 2015. pp. 222-226
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