Twitter fake account detection

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Date

2017

Authors

Journal Title

Journal ISSN

Volume Title

Publisher

Institute of Electrical and Electronics Engineers Inc.

Abstract

Social 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.

Description

Keywords

Entropy , Learning systems , Classification methods , Entropy minimization , Fake detection , Social media , Social networking sites , Spam detection , Supervised discretization , Twitter , Social networking (online)

Citation

URI

http://akademikarsiv.cbu.edu.tr:4000/handle/123456789/15223

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