Twitter fake account detection

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dc.contributor.authorErşahin B.
dc.contributor.authorAktaş O.
dc.contributor.authorKilmç D.
dc.contributor.authorAkyol C.
dc.date.accessioned2024-07-22T08:10:24Z
dc.date.available2024-07-22T08:10:24Z
dc.date.issued2017
dc.description.abstractSocial networking sites such as Twitter and Facebook attracts millions of users across the world and their interaction with social networking has affected their life. This popularity in social networking has led to different problems including the possibility of exposing incorrect information to their users through fake accounts which results to the spread of malicious content. This situation can result to a huge damage in the real world to the society. In our study, we present a classification method for detecting the fake accounts on Twitter. We have preprocessed our dataset using a supervised discretization technique named Entropy Minimization Discretization (EMD) on numerical features and analyzed the results of the Naïve Bayes algorithm. © 2017 IEEE.
dc.identifier.DOI-ID10.1109/UBMK.2017.8093420
dc.identifier.urihttp://akademikarsiv.cbu.edu.tr:4000/handle/123456789/15223
dc.language.isoEnglish
dc.publisherInstitute of Electrical and Electronics Engineers Inc.
dc.subjectEntropy
dc.subjectLearning systems
dc.subjectClassification methods
dc.subjectEntropy minimization
dc.subjectFake detection
dc.subjectSocial media
dc.subjectSocial networking sites
dc.subjectSpam detection
dc.subjectSupervised discretization
dc.subjectTwitter
dc.subjectSocial networking (online)
dc.titleTwitter fake account detection
dc.typeConference paper

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