<p>Social networking sites have become extremely popular in the past few years because of their extensible online connectivity and information sharing capabilities. The ability to communicate and connect online easily has attracted millions of users. Although this establishes high connectivity, privacy of user data is at stake due to various privacy threats such as sensitive data revelation, fake identities etc. We propose an automated dynamic grouping system to have better control over sensitive data that is shared online. This system analyses friends in social networking sites and categorizes them into best friends, normal friends and visitors. The categorization is based on various interaction parameters. The automated grouping system is enhanced using a recommendation system to make the system dynamic.</p>
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Dr. Shyamala C. K., Hemaashri, S., and Swetha, R., “An improved recommendation system for social networks”, International Journal of Control Theory and Applications, vol. 8, pp. 1903-1910, 2015.