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All liaisons are dangerous when all your friends are known to us
dc.contributor.author | Gayo Avello, Daniel | spa |
dc.date.accessioned | 2013-01-30T12:37:55Z | |
dc.date.available | 2013-01-30T12:37:55Z | |
dc.date.issued | 2011 | spa |
dc.identifier.isbn | 9781450302562 | spa |
dc.identifier.uri | http://hdl.handle.net/10651/12202 | |
dc.description.abstract | Abstract 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.extent | p. 171-180 | spa |
dc.language.iso | eng | |
dc.publisher | ACM | |
dc.relation.ispartof | HT 2011 - Proceedings of the 22nd ACM Conference on Hypertext and Hypermedia | spa |
dc.rights | © 2011 ACM | |
dc.title | All liaisons are dangerous when all your friends are known to us | spa |
dc.type | conference output | spa |
dc.identifier.local | 20111013 | spa |
dc.identifier.doi | 10.1145/1995966.1995991 | spa |
dc.relation.publisherversion | http://dx.doi.org/10.1145/1995966.1995991 | |
dc.rights.accessRights | open access |
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