You tube spam comment detection using support vector machine and k–nearest neighbor

Aziz, Aqliima and Mohd Foozy, Cik Feresa and Palaniappan, Shamala and Suradi, Zurinah (2017) You tube spam comment detection using support vector machine and k–nearest neighbor. Indonesian Journal of Electrical Engineering and Computer Science, 12 (2). pp. 612-619. ISSN 2502-4752

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Abstract

Social networking such as YouTube, Facebook and others are very popular nowadays. The best thing about YouTube is user can subscribe also giving opinion on the comment section. However, this attract the spammer by spamming the comments on that videos. Thus, this study develop a YouTube detection framework by using Support Vector Machine (SVM) and K-Nearest Neighbor (k-NN). There are five (5) phases involved in this research such as Data Collection, Pre-processing, Feature Selection, Classification and Detection. The experiments is done by using Weka and RapidMiner. The accuracy result of SVM and KNN by using both machine learning tools show good accuracy result. Others solution to avoid spam attack is trying not to click the link on comments to avoid any problems

Item Type:	Article
Uncontrolled Keywords:	Classification; Detection; Machine Learning; YouTube Spam
Subjects:	T Technology > T Technology (General) T Technology > TK Electrical engineering. Electronics Nuclear engineering > TK7800-8360 Electronics
Divisions:	Faculty of Computer Science and Information Technology > Department of Information Security
Depositing User:	Miss Nur Rasyidah Rosli
Date Deposited:	23 Dec 2021 06:57
Last Modified:	23 Dec 2021 06:57
URI:	http://eprints.uthm.edu.my/id/eprint/4905

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