A Survey of Spam Detection Methods on Twitter

Basit Öğe Kaydı
dc.contributor.authorKabakuş, Abdullah Talha
dc.contributor.authorKara, Resul
dc.date.accessioned2020-04-30T22:38:54Z
dc.date.available2020-04-30T22:38:54Z
dc.date.issued2017
dc.departmentDÜ, Mühendislik Fakültesi, Bilgisayar Mühendisliği Bölümüen_US
dc.descriptionKabakus, Abdullah Talha/0000-0003-2181-4292en_US
dc.descriptionWOS: 000400159400005en_US
dc.description.abstractTwitter is one of the most popular social media platforms that has 313 million monthly active users which post 500 million tweets per day. This popularity attracts the attention of spammers who use Twitter for their malicious aims such as phishing legitimate users or spreading malicious software and advertises through URLs shared within tweets, aggressively follow/unfollow legitimate users and hijack trending topics to attract their attention, propagating pornography. In August of 2014, Twitter revealed that 8.5% of its monthly active users which equals approximately 23 million users have automatically contacted their servers for regular updates. Thus, detecting and filtering spammers from legitimate users are mandatory in order to provide a spam-free environment in Twitter. In this paper, features of Twitter spam detection presented with discussing their effectiveness. Also, Twitter spam detection methods are categorized and discussed with their pros and cons. The outdated features of Twitter which are commonly used by Twitter spam detection approaches are highlighted. Some new features of Twitter which, to the best of our knowledge, have not been mentioned by any other works are also presented.en_US
dc.identifier.endpage38en_US
dc.identifier.issn2158-107X
dc.identifier.issn2156-5570
dc.identifier.issue3en_US
dc.identifier.startpage29en_US
dc.identifier.urihttps://hdl.handle.net/20.500.12684/2509
dc.identifier.volume8en_US
dc.identifier.wosqualityN/Aen_US
dc.indekslendigikaynakWeb of Scienceen_US
dc.language.isoenen_US
dc.publisherScience & Information Sai Organization Ltden_US
dc.relation.ispartofInternational Journal Of Advanced Computer Science And Applicationsen_US
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanıen_US
dc.rightsinfo:eu-repo/semantics/closedAccessen_US
dc.subjectTwitter spamen_US
dc.subjectspam detectionen_US
dc.subjectspam filteringen_US
dc.subjectmobile securityen_US
dc.titleA Survey of Spam Detection Methods on Twitteren_US
dc.typeArticleen_US

Dosyalar

Orijinal paket
Listeleniyor 1 - 1 / 1
Küçük Resim Yok
İsim:
2509.pdf
Boyut:
431.06 KB
Biçim:
Adobe Portable Document Format
Açıklama:
Tam Metin / Full Text
İndir

Koleksiyon

WoS İndeksli Yayınlar Koleksiyonu
Makale Koleksiyonu