When: Friday, March 11th, from 11 to 12 AM
Where: Turing building
Social content such as blogs, tweets, news etc. is a rich source of interconnected information. We identify a set of requirements for the meaningful exploitation of such rich content, and present a new data model, called S3, which is the first to satisfy them. S3 captures social relationships between users, and between users and content, but also the structure present in rich social content, as well as its semantics. We show how S3 instances are derived from content and relationships present in today’s social media, and provide the first top-k keyword search algorithm taking into account the social, structured, and semantic dimensions and formally establish its termination and correctness.
Experiments on real social networks demonstrate the efficiency and qualitative advantage of our algorithm through the joint exploitation of the social, structured, and semantic dimensions of S3.