preprintJan 1, 2013Closed access

4 Community Detection in Networks with Node Attributes

JYJaewon YangJMJulian McauleyJLJure Leskovec

Abstract

Abstract—Community detection algorithms are fundamental tools that allow us to uncover organizational principles in networks. When detecting communities, there are two possible sources of information one can use: the network structure, and the features and attributes of nodes. Even though communities form around nodes that have common edges and common attributes, typically, algorithms have only focused on one of these two data modalities: community detection algorithms traditionally focus only on the network structure, while clustering algorithms mostly consider only node attributes. In this paper, we develop Com-munities from Edge Structure and Node Attributes (CESNA), an accurate and scalable algorithm for…

Citation impact

791
total citations
FWCI
39.88
Percentile
100%
References
57
Citations per year

Authors

3
  • JY
    Jaewon YangCorresponding
  • JM
    Julian Mcauley
  • JL
    Jure Leskovec

Topics & keywords

Keywords
  • Computer science
  • Community structure
  • Robustness (evolution)
  • Data mining
  • Node (physics)
  • Cluster analysis
  • Focus (optics)
  • Scalability
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