The link-prediction problem for social networks

by: David Liben-Nowell, Jon Kleinberg

Journal of the American Society for Information Science and Technology, Vol. 58, No. 7. (2007), pp. 1019-1031.

View FullText article

Reviews [Write a review of this article]

There are no reviews of this article

Find related articles from these CiteULike users

elsantosneto, ldietz, merazzle, iris_2001, cursonivel1, theus, cursonivel1 (group), Social Web (group), amirmz, haveuheard, rrbarb, lfriedl, tnhh

Find related articles with these CiteULike tags

496, 62062016, ali, analysis, community-detection, lecture-10, link, linkmining, linkprediction, link_prediction, link-prediction, network, networks, pagerank, prediction, problema, reputation, sns, social, social-network-analysis, socialnetworks, social-networks

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.

@article{libennowell:link, 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.}, address = {Department of Computer Science, Carleton College, Northfield, MN 55057; Department of Computer Science, Cornell University, Ithaca, NY 14853}, author = {Liben-Nowell, David and Kleinberg, Jon }, citeulike-article-id = {1281581}, doi = {http://dx.doi.org/10.1002/asi.20591}, journal = {Journal of the American Society for Information Science and Technology}, keywords = {analysis, community-detection, social-networks}, number = {7}, pages = {1019--1031}, posted-at = {2008-07-22 13:10:47}, priority = {4}, title = {The link-prediction problem for social networks}, url = {http://dx.doi.org/10.1002/asi.20591}, volume = {58}, year = {2007} }

RIS record

TY - JOUR ID - libennowell:link L3 - citeulike-article-id:1281581 TI - The link-prediction problem for social networks JF - Journal of the American Society for Information Science and Technology VL - 58 IS - 7 SP - 1019 EP - 1031 AD - Department of Computer Science, Carleton College, Northfield, MN 55057; Department of Computer Science, Cornell University, Ithaca, NY 14853 N2 - 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. KW - analysis KW - community-detection KW - social-networks AU - Liben-Nowell, David AU - Kleinberg, Jon PY - 2007/// UR - http://dx.doi.org/10.1002/asi.20591 ER -

RIS BibTeX