Talash: Friend Finding In Federated Social Networks

In large online social networks, Friend Recommendation has evolved into an interesting problem. We try to find known acquaintances and new interesting friends on a Federated Social Network (FSN) , using StatusNet as our platform. FSNs are decentralized networks on the internet which can interoperate using the OStatus Suite of protocols. Friend finding on these networks is hard because we do not know the existence of other social networks or Users. We show how Linked Data representation like FOAF can solve this problem. We devise a model for the Federated Network centered around a User and use it to define the problem of Friend Finding. The solution uses two phases, first known as Quick Connect which tries to find old acquaintances. The second phase, Delayed Connect uses the Social Graph of Users to find prospective friends. We show how the FSN information centered around a User can be extracted from FOAF entries and generate new recommendations. We shall illustrate the working of Talash as a part of StatusNet. We experimented on the existing FSN and collected feedback from its Users. The results are encouraging and open new avenues for Friend Finding on the Internet. To the best of our knowledge, this is the first study of Federated Social Networks and the problem of Friend Finding in them.