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PLoS One. 2012;7(4):e34740. doi: 10.1371/journal.pone.0034740. Epub 2012 Apr 6.

One plus one makes three (for social networks).

Author information

1
Interdisciplinary Center for Scientific Computing (IWR), University of Heidelberg, Heidelberg, Germany.

Erratum in

  • PLoS One. 2012:7(4): doi/10.1371/annotation/c2a07195-0843-4d98-a220-b1c5b77a7e1a. Horvát, Emöke-Ágnes [corrected to Horvát, Emőke-Ágnes].

Abstract

Members of social network platforms often choose to reveal private information, and thus sacrifice some of their privacy, in exchange for the manifold opportunities and amenities offered by such platforms. In this article, we show that the seemingly innocuous combination of knowledge of confirmed contacts between members on the one hand and their email contacts to non-members on the other hand provides enough information to deduce a substantial proportion of relationships between non-members. Using machine learning we achieve an area under the (receiver operating characteristic) curve (AUC) of at least 0.85 for predicting whether two non-members known by the same member are connected or not, even for conservative estimates of the overall proportion of members, and the proportion of members disclosing their contacts.

PMID:
22493713
PMCID:
PMC3321038
DOI:
10.1371/journal.pone.0034740
[Indexed for MEDLINE]
Free PMC Article

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