Research data is experiencing a seemingly endless increase in both volume and production rate. At the same time, efficiently transferring, storing, and analyzing large scale research data have become major research foci. In this paper, we expand on our approach to sharing data for e-Science: a Social Content Delivery Network (S-CDN). A S-CDN leverages the social networks of researchers to automatically share data and place replicas on peers' resources based upon the premises of trust and interest in shared data. We denote a consumer of shared data as a data follower, similar to the notion of Twitter followers, except we add the element of bilateral authorization to capture a notion of trust. We describe a prototypical implementation for a S-CDN that captures an efficient asynchronous transfer mechanism for data management and replication. In addition, we study via simulation the interplay of user behavior with different replication strategies that capture social as well as more general premises for data sharing. Our results illustrate the opportunities and pitfalls of various replication and data access management strategies. Specifically, we show that socially-informed replication strategies are competitive with more general strategies in terms of availability, and outperform them in terms of spatial efficiency.