Paper Info
Title
Spam Detection in Social Media Employing Machine Learning Tool for Text Mining.
Abstract
In recent time, online social networks have been affected by various unwanted threats. Although they provided us with an open platform to share our thoughts with others, however, due to misuse of this powerful resource, general users are in endangered condition. For example, YouTube has been used as a promotional ground by various artist to upload their music videos, movie trailers, etc. and viewers can post their opinion on them. Unfortunately, often malicious users use to post phishing website links, advertisements, and fraudulent information in the comments section, which may transmit viruses or malwares. So, these harmful comments need to be identified in order to continue flawless service of social media. In this study, we have been implemented several classification algorithm to sort out the spam comments on YouTube videos from the legitimate one, their performance measures have been analysed as well as performance of ensemble classifier over single classifier algorithm in the context of text classification has also been highlighted.
Year
Venue
Field
2017
SITIS
Data modeling,World Wide Web,Social media,Open platform,Social network,Pattern recognition,Phishing,Computer science,sort,Upload,Artificial intelligence,Classifier (linguistics)
DocType
Citations 
PageRank 
Conference
0
0.34
References 
Authors
0
2
Name
Order
Citations
PageRank
Sadia Sharmin1152.45
Zakia Zaman200.68