Graduation Year

2010

Document Type

Thesis

Degree

M.S.C.S.

Degree Granting Department

Computer Science

Major Professor

Adriana Iamnitchi, Ph.D.

Keywords

Data management, Peer-to-peer systems, Social graph, Socially-aware applications, Privacy protection

Abstract

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.

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