Online Social Networks: Measurement, Analysis, and Applications to Distributed Information Systems

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Online Social Networks: Measurement, Analysis, and Applications to Distributed Information Systems ( online-social-networks-measurement-analysis-and-applications )

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10 growing dilemma. Most online social networks today allow only very coarse-grained content sharing policies: users typically have the options of sharing content with (subsets of) their direct friends or with everyone. Communities can provide a natural middle ground, allowing convenient sharing among groups of users who do not necessarily know each other but who are close together in the social network. Also, communities often represent sets of users with common interests, a fact that can be naturally leveraged by systems to provide information that is relevant at a local, rather than global, scope. Using empirical data from an online social network and from a system deployment, we demonstrate the potential for using communities in online social networks. We have built and deployed PeerSpective, a system that leverages communities in a so- cial network in order to aid Web search. PeerSpective automatically indexes browsed pages and transparently inserts relevant pages viewed by friends into Web search re- sults. The results are aggregated over the community and presented alongside the normal search results. Using data from a PeerSpective deployment, we demonstrate that communities represent groups of users with shared interests, and that PeerSpec- tive provides a measurable improvement to Web search. Finally, Chapter 10 presents concluding remarks, discusses the implications of our work, and describes future research directions.

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