Classification of fake news using multi-layer perceptron

dc.authorid0000-0002-1871-5691en_US
dc.contributor.authorJehad, Reham
dc.contributor.authorYousif, Suhad A.
dc.date.accessioned2024-07-12T20:54:25Z
dc.date.available2024-07-12T20:54:25Z
dc.date.issued2021en_US
dc.departmentMaltepe Üniversitesi, İnsan ve Toplum Bilimleri Fakültesien_US
dc.description.abstractt. "Fake News (FNs) is defined as a made-up story to deceive or to mislead." The problem of FNs spread widely in recent years, especially on social media such as Facebook, Twitter, and other sources like webs and blogs. It has become a significant problem in society as a result of changing people’s ideas and opinions about the direction of this news. In this paper, FNs detection can be proposed by using the Term Frequency-Inverse Document Frequency (TF-IDF) as features extraction, and Multi-Layer perceptron (MLP) algorithm as a classifier. Two phases (feed-forward and back-propagation) are used with a three-layers, which are (input layer, one hidden layer, and output layer). After running our proposed algorithm on a FNs dataset, the classification accuracy achieved equals 95.47%.en_US
dc.identifier.citationJehad, R. ve Yousif, S. A. (2021). Classification of fake news using multi-layer perceptron. Fourth International Conference of Mathematical Sciences, Maltepe Üniversitesi. s. 1-5.en_US
dc.identifier.endpage5en_US
dc.identifier.isbn978-0-7354-4078-4
dc.identifier.startpage1en_US
dc.identifier.urihttps://aip.scitation.org/doi/10.1063/5.0042264
dc.identifier.urihttps://hdl.handle.net/20.500.12415/2757
dc.language.isoenen_US
dc.publisherMaltepe Üniversitesien_US
dc.relation.ispartofFourth International Conference of Mathematical Sciencesen_US
dc.relation.isversionof10.1063/5.0042264en_US
dc.relation.publicationcategoryUluslararası Konferans Öğesi - Başka Kurum Yazarıen_US
dc.rightsCC0 1.0 Universal*
dc.rightsinfo:eu-repo/semantics/openAccessen_US
dc.rights.urihttp://creativecommons.org/publicdomain/zero/1.0/*
dc.snmzKY07341
dc.subjectMulti Layer Perceptronen_US
dc.subjectNLPen_US
dc.subjectTF-IDFen_US
dc.subjectFake news detectionen_US
dc.subjecttext classificationen_US
dc.subjectNews articles dataseten_US
dc.titleClassification of fake news using multi-layer perceptronen_US
dc.typeConference Object
dspace.entity.typePublication

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