Sentiment Analysis of Twitter: Turkey Earthquake 2023 Case

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dc.contributor.authorRashid, A.K.
dc.contributor.authorFindik, O.
dc.date.accessioned2024-09-29T16:22:39Z
dc.date.available2024-09-29T16:22:39Z
dc.date.issued2024
dc.departmentKarabük Üniversitesien_US
dc.description1st International Conference on Smart Automation and Robotics for Future Industry, SMARTINDUSTRY 2024 -- 18 April 2024 through 20 April 2024 -- Lviv -- 200057en_US
dc.description.abstractThe most devastating earthquake in the past 20 years was February 6, 2023. The earthquake occurred in southern Turkey near the northern Syrian border. Thousands of people died and many more were left homeless, due to the magnitude of the event, it quickly spread all over the world. The earthquake and its damage were discussed and analyzed from all sides. In this paper, a separate analysis was proposed for tweets posted within 14 days after the earthquake. In this analysis to classify tweets, one type of label did not depend as in previous works that have been done on text classification, but three different types of labels (Manual label, NLTK_VADER label, and Cluster label) are created to classify text tweets by using machine learning algorithms. Then by using the Jaccard similarity coefficient and the cosine similarity measure the two AI labels (NLTK_VADER and Cluster) are compared which result is closer to manual labeling, according to the number of categories (positive, negative, and natural) and accuracy of sentiment in each label. In the result, we have reached that the accuracy of the VADER labeling is more effective than Cluster labeling because its accuracy is much closer to the Manual labeling. © 2024 Copyright for this paper by its authors.en_US
dc.description.sponsorshipMy brother Engineer Amanj Kamal in Iraqen_US
dc.identifier.endpage208en_US
dc.identifier.issn1613-0073
dc.identifier.scopus2-s2.0-85195899509en_US
dc.identifier.scopusqualityN/Aen_US
dc.identifier.startpage198en_US
dc.identifier.urihttps://hdl.handle.net/20.500.14619/10183
dc.identifier.volume3699en_US
dc.indekslendigikaynakScopusen_US
dc.language.isoenen_US
dc.publisherCEUR-WSen_US
dc.relation.ispartofCEUR Workshop Proceedingsen_US
dc.relation.publicationcategoryKonferans Öğesi - Uluslararası - Kurum Öğretim Elemanıen_US
dc.rightsinfo:eu-repo/semantics/closedAccessen_US
dc.subjectClusteren_US
dc.subjectMachine learningen_US
dc.subjectNLTK VADERen_US
dc.subjectText classificationen_US
dc.subjectTurkey Earthquakeen_US
dc.titleSentiment Analysis of Twitter: Turkey Earthquake 2023 Caseen_US
dc.typeConference Objecten_US

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