Given a snapshot of a social network, can we infer which new interactions among its members are likely to occur in the near future? We formalize this question as the \emph{link prediction problem}, and develop approaches to link prediction based on measures of the ``proximity'' of nodes in a network. Experiments on large co-authorship networks suggest that information about future interactions can be extracted from network topology alone, and that fairly subtle measures for detecting node proximity can outperform more direct measures.