%0 Journal Article %1 libennowell2007linkprediction %A Liben-Nowell, David %A Kleinberg, Jon %D 2007 %I Wiley Subscription Services, Inc., A Wiley Company %J Journal of the American Society for Information Science and Technology %K analysis link network paper prediction research science sna social %N 7 %P 1019--1031 %R 10.1002/asi.20591 %T The link-prediction problem for social networks %U http://dx.doi.org/10.1002/asi.20591 %V 58 %X 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 link-prediction problem, and we develop approaches to link prediction based on measures for analyzing the “proximity” of nodes in a network. Experiments on large coauthorship 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.

@article{libennowell2007linkprediction, abstract = {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 link-prediction problem, and we develop approaches to link prediction based on measures for analyzing the “proximity” of nodes in a network. Experiments on large coauthorship 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.}, added-at = {2017-06-12T12:10:56.000+0200}, author = {Liben-Nowell, David and Kleinberg, Jon}, biburl = {https://www.bibsonomy.org/bibtex/21c8e2e0414084da508e98c9a8e5372fc/jaeschke}, description = {The link-prediction problem for social networks - Liben-Nowell - 2007 - Journal of the Association for Information Science and Technology - Wiley Online Library}, doi = {10.1002/asi.20591}, interhash = {2cb8581abd1a9cb0d0090946a72da080}, intrahash = {1c8e2e0414084da508e98c9a8e5372fc}, issn = {1532-2890}, journal = {Journal of the American Society for Information Science and Technology}, keywords = {analysis link network paper prediction research science sna social}, number = 7, pages = {1019--1031}, publisher = {Wiley Subscription Services, Inc., A Wiley Company}, timestamp = {2017-06-12T12:10:56.000+0200}, title = {The link-prediction problem for social networks}, url = {http://dx.doi.org/10.1002/asi.20591}, volume = 58, year = 2007 }