Online Community Detection By Spectral Cusum
Liyan Xie, Minghe Zhang, Yao Xie
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04 May 2020
We present an online community change detection algorithm called {\it spectral CUSUM} to detect the emergence of a community using a subspace projection procedure based on a Gaussian model setting. Theoretical analysis is provided to characterize the average run length (ARL) and expected detection delay (EDD), as well as the asymptotic optimality. Simulation and real data examples demonstrate the good performance of the proposed method.
