Please use this identifier to cite or link to this item: https://hdl.handle.net/11147/7791
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dc.contributor.authorSezerer, Erhan-
dc.contributor.authorPolatbilek, Ozan-
dc.contributor.authorTekir, Selma-
dc.date.accessioned2020-07-18T03:35:05Z-
dc.date.available2020-07-18T03:35:05Z-
dc.date.issued2019-
dc.identifier.isbn9781728119045-
dc.identifier.urihttps://doi.org/10.1109/SIU.2019.8806315-
dc.identifier.urihttps://hdl.handle.net/11147/7791-
dc.description27th Signal Processing and Communications Applications Conference, SIU 2019 -- 24 April 2019 through 26 April 2019en_US
dc.description.abstractAuthor profiling is the characterization of an author through some key attributes such as gender, age, and language. It's an indispensable task especially in security and marketing. In this work, the gender of a Twitter user is predicted using his/her tweets. A model combining a recurrent neural network (RNN) with an attention mechanism is proposed. As far as we know such a predictive analytics is performed in Turkish Twitter dataset for the first time, and the proposed model is tested in Turkish, English, Spanish, and Arabic with accuracy scores of 80.63, 81.73, 78.22, 78.5 respectively. The accuracy values obtained exhibit state-of-the-art in Turkish and competitive performance in the other languages. © 2019 IEEE.en_US
dc.description.abstractYazar ayrımlaması, yazarı bilinmeyen bir metin üzerinden yazarına dair cinsiyet, yaş ve dil gibi bazı anahtar özniteliklerin belirlenmesidir. Özellikle güvenlik ve pazarlama alanında önem arz etmektedir. Bu çalışmada, kullanıcıların tweetleri kullanılarak cinsiyetleri tahminlenmektedir. Yinelemeli Sinir Ağı (YSA) ve ilgi mekanizmasının birleşiminden oluşan bir model önerilmiştir. Bildiğimiz kadarıyla bu çalışma Twitter veri kümesi ile Türkçe’de ilk defa yapılmıştır. Önerilen model Türkçe, İngilizce, İspanyolca ve Arapça dillerinde sınanmış ve sırasıyla 80.63, 81.73, 78.22, 78.5 doğruluk değerlerine ulaşılmıştır. Elde edilen doğruluk değerleri Türkçe’de en gelişkin, diğer dillerde ise rekabetçi bir başarım ortaya koymaktadır.-
dc.language.isotren_US
dc.publisherInstitute of Electrical and Electronics Engineers Inc.en_US
dc.relation.ispartof27th Signal Processing and Communications Applications Conference, SIU 2019en_US
dc.rightsinfo:eu-repo/semantics/openAccessen_US
dc.subjectAttention mechanismen_US
dc.subjectAuthor profilingen_US
dc.subjectDeep learningen_US
dc.subjectGender predictionen_US
dc.subjectNeural networksen_US
dc.subjectTwitter dataseten_US
dc.titleTürkçe tweetler üzerinden yapay sinir ağları ile cinsiyet tahminlemesien_US
dc.title.alternativeGender prediction from Turkish tweets with neural networksen_US
dc.typeConference Objecten_US
dc.institutionauthorSezerer, Erhan-
dc.institutionauthorPolatbilek, Ozan-
dc.institutionauthorTekir, Selma-
dc.institutionauthorSezerer, Erhan-
dc.institutionauthorPolatbilek, Ozan-
dc.institutionauthorTekir, Selma-
dc.departmentİzmir Institute of Technology. Computer Engineeringen_US
dc.identifier.wosWOS:000518994300049en_US
dc.identifier.scopus2-s2.0-85071983297en_US
dc.relation.publicationcategoryKonferans Öğesi - Uluslararası - Kurum Öğretim Elemanıen_US
dc.identifier.doi10.1109/SIU.2019.8806315-
dc.relation.doi10.1109/SIU.2019.8806315en_US
dc.coverage.doi10.1109/SIU.2019.8806315en_US
item.openairetypeConference Object-
item.openairecristypehttp://purl.org/coar/resource_type/c_18cf-
item.fulltextWith Fulltext-
item.languageiso639-1tr-
item.cerifentitytypePublications-
item.grantfulltextopen-
crisitem.author.dept03.04. Department of Computer Engineering-
crisitem.author.dept03.04. Department of Computer Engineering-
Appears in Collections:Computer Engineering / Bilgisayar Mühendisliği
Scopus İndeksli Yayınlar Koleksiyonu / Scopus Indexed Publications Collection
WoS İndeksli Yayınlar Koleksiyonu / WoS Indexed Publications Collection
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