IWD Based Feature Selection Algorithm for Sentiment Analysis

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dc.authoridSarac, Esra/0000-0002-2503-0084
dc.contributor.authorParlar, Tuba
dc.contributor.authorSarac, Esra
dc.date.accessioned2025-01-06T17:37:51Z
dc.date.available2025-01-06T17:37:51Z
dc.date.issued2019
dc.description.abstractFeature selection methods aim to improve the classification performance by eliminating non-valuable features. In this paper, our aim is to apply a recent optimization technique namely the Intelligent Water Drops (IWD) algorithm to select best features for sentiment analysis. We investigate the classification performances of our proposed IWD based feature selection method by comparing one of the well-known feature selection method using Maximum Entropy classifier. Experimental results show that Intelligent Water Drops based feature selection method outperforms than ReliefF method for sentiment analysis.
dc.description.sponsorshipMustafa Kemal University Academic Research Project Unit [15426]
dc.description.sponsorshipThis research is supported by Mustafa Kemal University Academic Research Project Unit (No. 15426).
dc.identifier.doi10.5755/j01.eie.25.1.22736
dc.identifier.endpage58
dc.identifier.issn1392-1215
dc.identifier.issue1
dc.identifier.scopus2-s2.0-85061600093
dc.identifier.scopusqualityQ3
dc.identifier.startpage54
dc.identifier.urihttps://doi.org/10.5755/j01.eie.25.1.22736
dc.identifier.urihttps://hdl.handle.net/20.500.14669/2391
dc.identifier.volume25
dc.identifier.wosWOS:000458506100009
dc.identifier.wosqualityQ4
dc.indekslendigikaynakWeb of Science
dc.indekslendigikaynakScopus
dc.language.isoen
dc.publisherKaunas Univ Technology
dc.relation.ispartofElektronika Ir Elektrotechnika
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanı
dc.rightsinfo:eu-repo/semantics/openAccess
dc.snmzKA_20241211
dc.subjectFeature selection
dc.subjectMachine learning
dc.subjectNatural language processing
dc.subjectText mining
dc.subjectSentiment analysis
dc.titleIWD Based Feature Selection Algorithm for Sentiment Analysis
dc.typeArticle

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