Degree Granting Department
Adriana Iamnitchi, Ph.D.
Cristian Borcea, Ph.D.
Jay Ligatti, Ph.D.
Data Management, Peer-to-Peer Systems, Social Graph, Socially-Aware Applications, Privacy Protection
Applications and services that take advantage of social data usually infer social relationships using information produced only within their own context, using a greatly simplified representation of users' social data. We propose to combine social information from multiple sources into a directed and weighted social multigraph in order to enable novel socially-aware applications and services. We present GeoS, a geo-social data management service which implements a representative set of social inferences and can run on a decentralized system. We demonstrate GeoS' potential for social applications on a collection of social data that combines collocation information and Facebook friendship declarations from 100 students. We demonstrate its performance by testing it both on PlanetLab and a LAN with a realistic workload for a 1000 node graph.
Scholar Commons Citation
Anderson, Paul, "GeoS: A Service for the Management of Geo-Social Information in a Distributed System" (2010). Graduate Theses and Dissertations.