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All liaisons are dangerous when all your friends are known to us

dc.contributor.authorGayo Avello, Daniel spa
dc.date.accessioned2013-01-30T12:37:55Z
dc.date.available2013-01-30T12:37:55Z
dc.date.issued2011spa
dc.identifier.isbn9781450302562spa
dc.identifier.urihttp://hdl.handle.net/10651/12202
dc.description.abstractAbstract Online Social Networks (OSNs) are used by millions of users worldwide. Academically speaking, there is little doubt about the usefulness of demographic studies conducted on OSNs and, hence, methods to label unknown users from small labeled samples are very useful. However, from the general public point of view, this can be a serious privacy concern. Thus, both topics are tackled in this paper: First, a new algorithm to perform user profiling in social networks is described, and its performance is reported and discussed. Secondly, the experiments --conducted on information usually considered sensitive-- reveal that by just publicizing one's contacts privacy is at risk and, thus, measures to minimize privacy leaks due to social graph data mining are outlined
dc.format.extentp. 171-180spa
dc.language.isoeng
dc.publisherACM
dc.relation.ispartofHT 2011 - Proceedings of the 22nd ACM Conference on Hypertext and Hypermediaspa
dc.rights© 2011 ACM
dc.titleAll liaisons are dangerous when all your friends are known to usspa
dc.typeconference outputspa
dc.identifier.local20111013spa
dc.identifier.doi10.1145/1995966.1995991spa
dc.relation.publisherversionhttp://dx.doi.org/10.1145/1995966.1995991
dc.rights.accessRightsopen access


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