Diametrical User Control to Filter the Unwanted Messages from Online Social Networks

Online Social Networks (OSNs) are the most impulsive standard to provide communication, sharing and disseminate a significant amount of individual life data. Content can be changed based on daily needs in several communication fields (audio, video, image, and text). One of the important aspects of OSN is to give the user capacity to automatically manage the messages posted and also to filter the unnecessary messages. The main aim of my work is to evaluate an automated system called Filter walls and also using Machine learning text categorization technique. These techniques automatically label the messages in support of substance-based filtering. This application focuses on Face book where unknown persons post unwanted comments for the uploaded photos. So, our system provides help and security to our profiles by directly controlling what kind of messages should be posted on our own walls. 1