Data mining Framework for Finding Friends in Online Social Network Using Minimum Information
Abstract— Online Social Network such as Face book, Twitter, LinkedIn, have become the preferred interaction, entertainment and socializing facility on the internet. However With the emergence of numerous social media sites, individuals, with their limited time, often face a dilemma of choosing a few sites over others. Users prefer more engaging sites, where they can find familiar faces such as friends, relatives, or colleagues. Link predictions method help find friends using link or content information. Unfortunately, whenever users join any site, they have no friends or any content generated. In this case, sites have no chance other than recommending random influential users to individuals hoping that users by befriending them create sufficient information for link prediction techniques to recommend meaningful friends. In this paper, we discussed find friends on a new a social media site when link or content information is unavailable. The purpose of this research paper is highlighting social forces in Online Social Network using minimum information with their latest solutions by using data mining techniques are dealt in this paper elaborately.
Index Terms— Confounding, Compatibility, Homophily, Incompatibility, Influence, Social media, Social forces.
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International Journal for Trends in Technology & Engineering © 2015 IJTET JOURNAL