Community Detection in Degree-Corrected Block Models

Understand

Community detection is a central problem of network data analysis.

• Given a network, the goal of community detection is to partition the network nodes into a small number of clusters, which could often help reveal interesting structures.
• The present paper studies community detection in Degree-Corrected Block Models (DCBMs).
• We first derive asymptotic minimax risks of the problem for a misclassification proportion loss under appropriate conditions.