Network Cross-Validation for Determining the Number of Communities in Network Data

• Activity Number: 490
• Type: Contributed
• Date/Time: Wednesday, August 12, 2015 : 8:30 AM to 10:20 AM
• Sponsor: IMS
• Author(s): Jing Lei* and Kehui Chen
• Companies: Carnegie Mellon University and University of Pittsburgh
• Keywords: network data ; community recovery ; model selection ; cross-validation ; stochastic block model

Abstract

We develop an efficient cross-validation approach to determine the number of communities, as well as to choose between the regular stochastic block model and the degree corrected block model. Our method, called network cross-validation, is based on a block-wise edge splitting technique, combined with an integrated step of community recovery using sub-blocks of the adjacency matrix. The performance of our method is supported by theoretical analysis of the sub-block parameter estimation. Extensions to more general network models are also discussed.