Social networking alternatively referred to as a virtual community or profile site, a social networking a website on the Internet that brings people together in a central location to talk, share ideas and interests, or make new friends. This type of collaboration and sharing of data is often referred to as social media. Unlike traditional media that is often created by not more than 10 people, social media sites contain content that has been created by hundreds or even millions of different people. Information filtering has been greatly explored for what considerations textual documents and website (5-7). However, the aim of bulk of those proposals is especially to supply users a classification mechanism to avoid useless information. In OSNs, data filtering may be used for a different, additional sensitive, purpose. This can bethink tithe very fact that in OSNs there’s likelihood of posting or commenting alternative posts on specific public/private areas, called normally walls. Data filtering will be used to provide users the flexibility to mechanically manage the messages written on their own walls, by filtering out unwanted messages. We have a tendency to believe that this can be a key in OSN service that has not been provided thus far. Indeed, today OSNs offer little support to forestall unwanted messages on user walls [8].

Depending on the application, one paradigm is likely to be more valuable than the other. For example, if the objective is to collect information on a certain topic, content-based filtering may be suitable. Yet, if the aim is to gather information in order to keep up to date with a certain community, collaborative filtering is more appropriate. Obviously, a collaborative filtering system is good at identifying novelty because it is guided by humans. However, this technique can only succeed when the users are not overloaded with information. One potential concern with the perspective architecture is the privacy of the users. Perspective indexes browsed, web pages, which sometimes contain sensitive information. In order to mitigate the privacy impact of Perspective on users, we configured Perspective to only serve HTTP, and specifically not HTTPS, traffic. As many privacy-sensitive services, such as online banking and email, use HTTPS, this prevents such sites from being indexed by Perspective. Below is a small list of some of the biggest social networks used today (1).

• Face book (http://www.facebook.com/) - One of the most popular social networking websites on the Internet. Face book is a popular destination for users to setup their own personal web pages, connect with friends, share pictures, share movies, talk about what you're doing, etc(2).

 LinkedIn (http://www.linkedin.com/) - One of the best if not the best locations to connect

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• Orkut (http://www.orkut.com/) - A popular service from Google that provides you a location to socialize with your friends and family, and meet new acquaintances from all around the world (2).

• Twitter (http://www.twitter.com/) - Another fantastic service that allows users to post 140 character long posts from their phones and on the Internet. A fantastic way to get the pulse of what's going on around the world (2).

• YouTube (http://www.youtube.com/) - A great network of users posting video blogs or Vlog's and other fun and interesting videos (2).

Refined and Secured Wall structural design is a three covered layered planning design that we use in our proposed system. The first layer is Social Network Manager (SNM) layer. This layer provides basic OSN functions of profile and association management. The second layer is a Social Network Application layer. It makes use of all the filtering techniques to spotless the unwanted messages. It includes the Filtering Policies, the Short Text Classifier, the data sent for endorsement to user friends, the approval of the text from those friends and the blacklist management. The real process of filtering is carried out here in this layer. The last layer is the GUI (Graphical User Interface) layer which provides the user to interact with each other via the OSN (Online Social Networks) (4). Figure1: Refined and Secured Wall Conceptual Architecture and flow messages from writing to publication of the messages on user walls.

During the last ten years, social networks have evolved from simple communication hubs to veritable agents of change; galvanizing thousands of people Just couple of years back, many people dismissed Face book as a place for kids to share their rants/pictures. Today, more than 600 million users worldwide are active on this website. Approximately 200 million people are active on twitter, another 100 million use LinkedIn. None of these social networks even excited at the beginning of the decade. Social networks have had lasting and arguably permanent effects.

• Politics and Public Service

Just as personal computers changed the face of businesses forever, social networks have altered the operational model of politics and public service. Face book has become the touchstone for how non-profit organizations, environmental activities, and political factions reach out to thousands of potential volunteers and donors.

• Marketing and Advertising

Marketing and advertising are transforming themselves from industries reliant on mass market channels to those that must embrace the power of the customer, and attempt to engage in conversations with them. Often, a “middle man” (such as newspaper reporter) ultimately determined that what was written or said.

• Business and Recruitment

Almost every credible business has a social presence today. Not only that, emerging businesses have adopted social networking sites to promote their products, services, and gain insightful feedback. It is not uncommon to see small or home grow businesses that operate solely through their Face book accounts. In fact, for businesses, interaction via social network has almost become a yardstick to test out their customer service (3).

Today, millions of people use information technology to work, play, read, learn, socialize, connect, and express themselves. This broad range of new applications inspired the work in this paper, where we have measured and analyzed the properties of online social networks, and designed, deployed, and evaluated new information systems that exploit the properties of these networks.

(1) V.Vaneesha, T.Sunitha, Efficiencies and Automated Process of refining the Unwanted Data from Online Social Networking, International Journal of Computer Trends

(2) http://www.computerhope.com/jargon/s/ socinetw.htm (3) http://www.whatissocialnetworking.com/ article11.html (4) Sampada More, Amol Dhanure, Alpana Kulkarni, Prakash B. Nimbalkar, Unwanted Text Filter for Online Social Networks (OSN), International Journal of Advanced Research in Computer Science and Software Engineering, Volume 5, Issue 2, February 2015 (5) Marco Vanetti, ElisabettaBinaghi, Elena Ferrari, Barbara Carminati, and Moreno Carullo, "A System to Filter Unwanted Messages from OSN User Walls" VOL. 25, NO. 2, FEBRUARY 2013. (6) A. Adomavicius and G. Tuzhilin, “Toward the Next Generation of Recommender Systems: A Survey of the State-of-the-Art and Possible Extensions,” IEEE Trans. Knowledge and Data Eng., vol. 17, no. 6, pp. 734-749, June 2005. (7) M. Chau and H. Chen, “A Machine Learning Approach to Web Page Filtering Using Content and Structure Analysis,” Decision Support Systems, vol. 44, no. 2, pp. 482-494, 2008. (8) Aniket Nandkumar Tirgul, Prof. Bere Sachin Sukhdev, A Rule Based System to Refine User Walls, International Journal on Recent and Innovation Trends in Computing and Communication, Volume: 3 Issue: 2, ISSN: 2321-8169 559 - 562