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Sms Spam Detection in Turkish Language
(MEF Üniversitesi, Fen Bilimleri Enstitüsü, 2018) Gürkan, Cem Kaya; Koç, Utku
Short message (SMS) is one of the most common communication methods. The growth of mobile phone users has led to a dramatic increase in using short messages. With the increasing number of mobile phone users, mobile phone users have started receiving unsolicited text messages. The use of SMS as a spam tool after the e-mail is due to a direct access to customer and high reversion to the users. These unsolicited short messages are disturbing the users even content intended for deceiving or defrauding (phishing). Up to date, all of the research carried out on SMS Spam detection was focused on the English language. In this study, Turkish datasets tagged with spam information is introduced and existing methods for English are applied to these datasets. The SMS dataset used in this study is gathered from different people and all messages are tagged according to whether they are spam or not. Naïve Bayes, Logistic Regression, SGD, SVM and Random Forest classification algorithms are tested with three feature extraction methods and a number of performance measures are evaluated. The evaluation resulted in a f-measure of 96.4% for SVM classification algorithm with TF-IDF (Term Frequency-Inverse Document Frequency) extraction method.

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