Open Access
2016 Community detection in networks with node features
Yuan Zhang, Elizaveta Levina, Ji Zhu
Electron. J. Statist. 10(2): 3153-3178 (2016). DOI: 10.1214/16-EJS1206


Many methods have been proposed for community detection in networks, but most of them do not take into account additional information on the nodes that is often available in practice. In this paper, we propose a new joint community detection criterion that uses both the network edge information and the node features to detect community structures. One advantage our method has over existing joint detection approaches is the flexibility of learning the impact of different features which may differ across communities. Another advantage is the flexibility of choosing the amount of influence the feature information has on communities. We show the method performs well on simulated and real networks.


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Yuan Zhang. Elizaveta Levina. Ji Zhu. "Community detection in networks with node features." Electron. J. Statist. 10 (2) 3153 - 3178, 2016.


Received: 1 October 2015; Published: 2016
First available in Project Euclid: 10 November 2016

zbMATH: 1359.62271
MathSciNet: MR3571965
Digital Object Identifier: 10.1214/16-EJS1206

Keywords: joint detection , Network communities , node features

Rights: Copyright © 2016 The Institute of Mathematical Statistics and the Bernoulli Society

Vol.10 • No. 2 • 2016
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