文章基本信息

标题：Prediction of Fake Profiles on Facebook using Supervised Machine Learning Techniques-A Theoretical Model.
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作者：Suheel Yousuf Wani ; Mudasir M Kirmani ; Syed Imamul Ansarulla 等
期刊名称：International Journal of Computer Science and Information Technologies
电子版ISSN：0975-9646
出版年度：2016
卷号：7
期号：4
页码：1735-1738
出版社：TechScience Publications
摘要：Facebook is a social networking site. This site haschanged the way people pursue social life and made it easy toconnect with family members, classmates, friends and colleagues.Based on the data available for the first quarter of 2016 facebookhas approximately 1.65 billion active users. However, the numberof fake profiles has increased manifold and research work ofdifferent researchers shows that 20% to 40% of the user profilesavailable on facebook are fake profiles. but with the fast growthof users, fake profiles/users has also grown. In order to detect andminimize the number of fake profiles on facebook very fewtechniques do exist. This research work is an effort to explain atheoretical model using which fake profiles can be detected onfacebook. The proposed model has used machine learningalgorithms like support vector machine(SVM), DecisionTree(DT), artificial neural networks(ANN) and Nave Bayaes (NB)to classify the user profiles into fake and genuine.
关键词：Machine Learning; fake profile detection; ensemble;classifier.