The link‐prediction problem for social networks

Carleton College · Cornell University

Indexed incrossref

Abstract

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.

Citation impact

3,014
total citations
FWCI
21.10
Percentile
100%
References
32
Citations per year

Authors

2

Topics & keywords

Keywords
  • Snapshot (computer storage)
  • Computer science
  • Link (geometry)
  • Network science
  • Node (physics)
  • Social network (sociolinguistics)
  • Data mining
  • Network topology
UN Sustainable Development Goals
  • Reduced inequalities
No related works found for this paper.