UTHM Institutional Repository

YouTube spam comment detection using support vector machine and K–nearest neighbor

Aziz, Aqliima and Mohd Foozy, Cik Feresa and Palaniappan, Shamala and Suradi, Zurinah (2018) YouTube spam comment detection using support vector machine and K–nearest neighbor. Indonesian Journal of Electrical Engineering and Computer Science, 12 (2). pp. 607-611. ISSN 25024752

Full text not available from this repository.

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: Q Science > QA Mathematics > QA76 Computer software
Divisions: Faculty of Computer Science and Information Technology > Department of Information Security
Depositing User: Mr. Mohammad Shaifulrip Ithnin
Date Deposited: 30 Apr 2019 01:05
Last Modified: 30 Apr 2019 01:05
URI: http://eprints.uthm.edu.my/id/eprint/10957
Statistic Details: View Download Statistic

Actions (login required)

View Item View Item