Centralized social networking websites raise scalability issues - due to the growing number of participants - and, as well as, policy concerns - such as control, privacy and ownership over the user's published data. Distributed Social Networks aim to solve this issue by enabling architecture where people own their data and share it their own way. However, the privacy and scalability challenge is still to be tackled. This paper presents a privacy-aware extension to Google's PubSubHubbub protocol, using Semantic Web technologies, solving both the scalability and the privacy issues in Distributed Social Networks. We enhanced the traditional feature of PubSubHubbub protocol - that decouples publishers and subscribers - in order to allow publishers to decide whom they want to share their information with. We also present a use-case of applying this to SMOB (our (Semantic Microblogging framework). Our architecture is application agnostic, and can be adopted by any system that requires scalable and privacy-aware content broadcasting.
Sheth, A. P.,
& Passant, A.
(2011). Privacy-Aware an Scalable Content Dissemination in Distributed Social Networks. Lecture Notes in Computer Science, 7032, 157-172.