Selective Propagation of Social Data in Decentralized Online Social Network

In Online Social Networks (OSNs) users are overwhelmed with huge amount of social data, most of which are irrelevant to their interest. Due to the fact that most current OSNs are centralized, people are forced to share their data with the site, in order to be able to share it with their friends, and thus they lose control over it. Decentralized OSNs provide an alternative which allows users to maintain control over their data. This paper discusses an approach for propagation of social data in a decentralized OSN so as to reduce irrelevant data among users. The approach uses interaction between users to construct relationship model of interest. This relationship model acts as a filter later while propagating social data of the same interest group. This paper also presents a plan of a simulation to analyze our approach.