Twitter Sentiment Analysis Based on Daily Covid-19 Table in Turkey

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dc.contributor.authorKaya, Buket
dc.contributor.authorGünay, Abdullah
dc.date.accessioned2024-12-24T19:18:05Z
dc.date.available2024-12-24T19:18:05Z
dc.date.issued2021
dc.departmentSiirt Üniversitesi
dc.description.abstractThe coronavirus epidemic, which began to affect the whole world in early 2020, has become the most talked about agenda item by individuals. Individuals announce their feelings and thoughts through various communication channels and receive news from what is happening around them. One of the most important channels of communication is Twitter. Individuals express their feelings and thoughts by interacting with the tweets posted. The aim of this study is to analyze the emotions of the comments made under the \"daily coronavirus table\" shared by the Republic of Turkey Ministry of Health and to measure their relationship with the daily number of cases and deaths. In the study, emotional classification of tweets was implemented using LSTM, GRU and BERT methods from deep learning algorithms, and the results of all three algorithms were compared with the daily number of cases and deaths.
dc.identifier.doi10.35377/saucis...932620
dc.identifier.endpage311
dc.identifier.issn2636-8129
dc.identifier.issue3
dc.identifier.startpage302
dc.identifier.trdizinid501654
dc.identifier.urihttps://doi.org/10.35377/saucis...932620
dc.identifier.urihttps://search.trdizin.gov.tr/tr/yayin/detay/501654
dc.identifier.urihttps://hdl.handle.net/20.500.12604/4925
dc.identifier.volume4
dc.indekslendigikaynakTR-Dizin
dc.language.isoen
dc.relation.ispartofSakarya University Journal of Computer and Information Sciences (Online)
dc.relation.publicationcategoryMakale - Ulusal Hakemli Dergi - Kurum Öğretim Elemanı
dc.rightsinfo:eu-repo/semantics/openAccess
dc.snmzKA_20241222
dc.subjectDeep Learnig
dc.titleTwitter Sentiment Analysis Based on Daily Covid-19 Table in Turkey
dc.typeArticle

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