A Customized Filter to apply on Online Social Network (OSN) user walls

Social networks hosted by a website are graphs of people where edges connect friends. Friendship represents shared interest or trust. A Network consists of one or more Nodes it could be Persons, Organizations, Groups, and Nations, Web Connected by One or More Ties. Users of these sites do not have much control to avoid unwanted content to be displayed on their own private space called in general wall. Therefore a major task of today’s online social network is information filtering. To control the abused words posting on a wall using the concept of Content Based Message Filtering (CBMF) and Machine learning Technique. The more sophisticated approach to decide when a user should be inserted in to a Blacklist is implemented by the User feedbacks. The user has the option to suggest people to add in the Blacklist. The particular user then searched in the Blacklist database suppose if the user exists then she/he would be blocked. Also, if the user feedback is more than 50% to block the same user then the user will be blocked. Additionally, before the comment is made public on the post or share made by the user, they have the option to block or approve it. This concept avoids the usage of abused words in the content and dissatisfaction of comments.