Classification of Unwanted E-Mails (Spam) with Turkish Text by Different Algorithms in Weka Program

Authors : Hüseyin ŞİMŞEK, Emrah AYDEMİR

Pages : 1-10

Doi:10.55195/jscai.1104694

View : 13 | Download : 16

Publication Date : 2022-06-28

Article Type : Research Paper

Abstract :Abstract: Today, with the widespread use of the Internet, electronic communication tools have also been widely used. One of these tools is e-mails. E-mails are easy to use and provide the opportunity to reach thousands of people at the same time. This advantage causes some bad uses. E-mail users are faced with dozens of unsolicited mails insert ignore into journalissuearticles values(spam); against their will. In this study, 1017 mails collected from about 20 different Gmail and Hotmail accounts were classified as spam or regular e-mail using the algorithms in the Weka program, and the success of the algorithms was compared. In the study, 45 different algorithms were tested. The highest classification success was obtained with the NavieBayesMultinominal and NavieBayesMultinominalUpdateable algorithms with 94.7886% correct classification. Among other classifier algorithms, Trees RandomForest algorithm 93.6087%, Meta. MultiClassClassifier and Functions SGD 92.4287%, Functions SMO 91.7404%, Meta RandomCommittee 91.0521%, Bayes NavieBayes and Bayes NavieBayesUpdateable 90.3638% classification success.
Keywords : E mail, Spam E mail, Weka, Classification Algorithm