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Community detection in networks with node features. (English) Zbl 1359.62271

Summary: 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.

MSC:

62H30 Classification and discrimination; cluster analysis (statistical aspects)
62H12 Estimation in multivariate analysis
05C82 Small world graphs, complex networks (graph-theoretic aspects)
91D30 Social networks; opinion dynamics
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