|Project Description: ||A lot of time of the internet user is invested on social network rather than search
engines. Many of the business organizations and celebrities are taking advantage of this
service by setting up social networking pages to improve direct communication with
online users. Social media heavily relies on user-generated content which makes them
incredibly powerful. In a very quick and effective way the information is passed across
YouTube. However, YouTube network is prone to various types of unnecessary and
malicious spammer activities. To maximize the popularity of a video, spammers post
comments and video links, where the comment has irrelevant content of the subject being
discussed. If spams are left unchecked, it attenuates resources sharing, inter
communication and openness. Hence there is a crucial need for security solution and a
technique to combat video spamming in YouTube.
In this proposed system, the Naive Baye’s algorithm which is based on Baye’s
Theorem is used. In this system, using Tube kit, data of YouTube videos are collected
and manually categorizes it as legitimate or a spam video. Various attributes that could
lead to spammers are explored using TubeKit. Later Microsoft SQL Server Data Mining
Tools is used to determine if a video is legitimate or spam.