Tunisian Dialect Sentiment Analysis: A Natural Language Processing-based Approach

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dc.contributor.authorMulki, Hala
dc.contributor.authorHaddad, Hatem
dc.contributor.authorAli, Chedi Bechikh
dc.contributor.authorBabaoglu, Ismail
dc.date.accessioned2020-03-26T20:11:38Z
dc.date.available2020-03-26T20:11:38Z
dc.date.issued2018
dc.departmentSelçuk Üniversitesien_US
dc.description.abstractSocial media platforms have been witnessing a significant increase in posts written in the Tunisian dialect since the uprising in Tunisia at the end of 2010. Most of the posted tweets or comments reflect the impressions of the Tunisian public towards social, economical and political major events. These opinions have been tracked, analyzed and evaluated through sentiment analysis systems. In the current study, we investigate the impact of several preprocessing techniques on sentiment analysis using two sentiment classification models: Supervised and lexicon-based. These models were trained on three Tunisian datasets of different sizes and multiple domains. Our results emphasize the positive impact of preprocessing phase on the evaluation measures of both sentiment classifiers as the baseline was significantly outperformed when stemming, emoji recognition and negation detection tasks were applied. Moreover, integrating named entities with these tasks enhanced the lexicon-based classification performance in all datasets and that of the supervised model in medium and small sized datasets.en_US
dc.identifier.doi10.13053/CyS-22-4-3009en_US
dc.identifier.endpage1232en_US
dc.identifier.issn1405-5546en_US
dc.identifier.issn2007-9737en_US
dc.identifier.issue4en_US
dc.identifier.pmid#YOKen_US
dc.identifier.scopusqualityQ3en_US
dc.identifier.startpage1223en_US
dc.identifier.urihttps://dx.doi.org/10.13053/CyS-22-4-3009
dc.identifier.urihttps://hdl.handle.net/20.500.12395/37103
dc.identifier.volume22en_US
dc.identifier.wosWOS:000471008800015en_US
dc.identifier.wosqualityN/Aen_US
dc.indekslendigikaynakWeb of Scienceen_US
dc.indekslendigikaynakScopusen_US
dc.language.isoenen_US
dc.publisherIPN, CENTRO INVESTIGAVION COMPUTACIONen_US
dc.relation.ispartofCOMPUTACION Y SISTEMASen_US
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanıen_US
dc.rightsinfo:eu-repo/semantics/closedAccessen_US
dc.selcuk20240510_oaigen_US
dc.subjectTunisian sentiment analysisen_US
dc.subjecttext preprocessingen_US
dc.subjectnamed entitiesen_US
dc.titleTunisian Dialect Sentiment Analysis: A Natural Language Processing-based Approachen_US
dc.typeArticleen_US

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