  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.
