Developing a new ensemble method for sentiment analysis in mobile assisted language learning: a case study for Duolingo

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dc.authoridKekul, Hakan/0000-0001-6269-8713
dc.contributor.authorKekul, Hakan
dc.contributor.authorPolatgil, Mesut
dc.date.accessioned2025-05-04T16:45:57Z
dc.date.available2025-05-04T16:45:57Z
dc.date.issued2025
dc.departmentSivas Cumhuriyet Üniversitesi
dc.description.abstractIn today's world, mobile devices and mobile technologies have become one of the indispensable elements, especially for young people. Learning activities using these technologies have also become widespread, and mobile assisted language learning (MALL) has become even more important. This study was conducted to evaluate users' opinions about MALL methods. For this purpose, Duolingo user comments, which is currently the most known and used mobile application in foreign language education, were used. One million comments to the app are classified in terms of sentiment analysis. In the study, a new model was proposed by combining different feature extraction and classification methods and the results were compared. It has been determined that the proposed model has high classification success. With the proposed model, it is thought that user opinions can be analysed and software and applications can be developed according to user needs, especially for foreign language learning.
dc.identifier.doi10.1504/IJMLO.2025.145278
dc.identifier.issn1746-725X
dc.identifier.issn1746-7268
dc.identifier.issue2
dc.identifier.scopus2-s2.0-105001980142
dc.identifier.scopusqualityQ1
dc.identifier.urihttps://doi.org/10.1504/IJMLO.2025.145278
dc.identifier.urihttps://hdl.handle.net/20.500.12418/35302
dc.identifier.volume19
dc.identifier.wosWOS:001456733300006
dc.identifier.wosqualityN/A
dc.indekslendigikaynakWeb of Science
dc.indekslendigikaynakScopus
dc.language.isoen
dc.publisherInderscience Enterprises Ltd
dc.relation.ispartofInternational Journal of Mobile Learning and Organisation
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanı
dc.rightsinfo:eu-repo/semantics/closedAccess
dc.snmzKA_WOS_20250504
dc.subjectmobile assisted language learning
dc.subjectMALL
dc.subjectDuolingo
dc.subjectsentiment analysis
dc.subjectclassification
dc.subjectensemble machine learning
dc.titleDeveloping a new ensemble method for sentiment analysis in mobile assisted language learning: a case study for Duolingo
dc.typeArticle

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