Analysis of whether news on the Internet is real or fake by using deep learning methods and the TF-IDF algorithm

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dc.authoridhttps://orcid.org/0000-0002-6882-5004en_US
dc.authoridhttps://orcid.org/0000-0003-4535-3953en_US
dc.authoridhttps://orcid.org/0000-0002-0122-8512en_US
dc.authoridhttps://orcid.org/0000-0002-8039-2686en_US
dc.contributor.authorKorkmaz, Tilbe
dc.contributor.authorÇetinkaya, Ali
dc.contributor.authorAydın, Hakan
dc.contributor.authorBarışkan, Mehmet Ali
dc.date.accessioned2023-10-26T19:08:37Z
dc.date.available2023-10-26T19:08:37Z
dc.date.issued2021en_US
dc.departmentMühendislik ve Mimarlık Fakültesien_US
dc.description.abstractInternet use has become increasingly widespread nowadays. In addition, there is a significant increase in the amount of text content produced in digital media. However, the accuracy and inaccuracy of the news we read and the content produced in a large number are also unknown. In this study, classification and analysis of whether the news is real or not were done by using Deep Learning methods. For the English news, the data set created by Katharine Jarmul was used. The data set contained a total of 6336 news items. The distribution of this data set, which consisted of political and political news, was 50% fake and 50% real. The method used in text classification was Term Frequency - Inverse Document Frequency (TF-IDF). The classification was made with the data set used and 93.88% success and 6.12% error were obtained as a result of the analysis.en_US
dc.identifier.doi10.35860/iarej.779019en_US
dc.identifier.endpage41en_US
dc.identifier.issn2618-575X
dc.identifier.issue1en_US
dc.identifier.startpage31en_US
dc.identifier.trdizinid425726en_US
dc.identifier.urihttps://hdl.handle.net/11363/6072
dc.identifier.urihttps://search.trdizin.gov.tr/tr/yayin/detay/425726
dc.identifier.urihttps://doi.org/
dc.identifier.volume5en_US
dc.indekslendigikaynakTR-Dizinen_US
dc.institutionauthorKorkmaz, Tilbe
dc.institutionauthorÇetinkaya, Ali
dc.institutionauthorAydın, Hakan
dc.institutionauthorBarışkan, Mehmet Ali
dc.language.isoenen_US
dc.publisherCeyhun Yılmazen_US
dc.relation.ispartofInternational Advanced Researches and Engineering Journalen_US
dc.relation.publicationcategoryMakale - Ulusal Hakemli Dergi - Kurum Öğretim Elemanıen_US
dc.rightsinfo:eu-repo/semantics/openAccessen_US
dc.rightsAttribution-NonCommercial-NoDerivs 3.0 United States*
dc.rights.urihttp://creativecommons.org/licenses/by-nc-nd/3.0/us/*
dc.subjectNatural language processingen_US
dc.subjectText analysisen_US
dc.subjectText classificationen_US
dc.subjectTF-IDF algorithmsen_US
dc.titleAnalysis of whether news on the Internet is real or fake by using deep learning methods and the TF-IDF algorithmen_US
dc.typeArticleen_US

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