Open AccessYouTube Spam Comment Detection Using Support Vector Machine and K–Nearest Neighbor
Author(s) -
Nor Azwan Mohamed Kamari,
Ismail Musirin,
Zulkiffli Abdul Hamid,
Ahmad Asrul Ibrahim
Publication year - 2018
Publication title -
indonesian journal of electrical engineering and computer science
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.241
H-Index - 17
eISSN - 2502-4760
pISSN - 2502-4752
DOI - 10.11591/ijeecs.v12.i2.pp612-619
Subject(s) - spamming , support vector machine , computer science , k nearest neighbors algorithm , machine learning , artificial intelligence , feature selection , feature (linguistics) , data mining , nearest neighbour , information retrieval , pattern recognition (psychology) , world wide web , the internet , linguistics , philosophy
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.