Null Models and Community Detection in Multi-Layer Networks

Subhadeep Paul, Yuguo Chen

Research output: Contribution to journalArticlepeer-review


Multi-layer networks of multiplex type represent relational data on a set of entities (nodes) with multiple types of relations (edges) among them where each type of relation is represented as a network layer. A large group of popular community detection methods in networks are based on optimizing a quality function known as the modularity score, which is a measure of the extent of presence of module or community structure in networks compared to a suitable null model. Here we introduce several multi-layer network modularity and model likelihood quality function measures using different null models of the multi-layer network, motivated by empirical observations in networks from a diverse field of applications. In particular, we define multi-layer variants of the Chung-Lu expected degree model as null models that differ in their modeling of the multi-layer degrees. We propose simple estimators for the models and prove their consistency properties. A hypothesis testing procedure is also proposed for selecting an appropriate null model for data. These null models are used to define modularity measures as well as model likelihood based quality functions. The proposed measures are then optimized to detect the optimal community assignment of nodes (Code available at: We compare the effectiveness of the measures in community detection in simulated networks and then apply them to four real multi-layer networks.

Original languageEnglish (US)
Pages (from-to)163-217
Number of pages55
JournalSankhya A
Issue number1
StatePublished - Jun 2022


  • 62F40
  • 62R07
  • 90B15
  • Configuration model
  • Primary 62F10
  • Secondary 62H30
  • degree corrected multi-layer stochastic block model
  • expected degree model
  • multi-layer network
  • multi-layer null models
  • multiplex network

ASJC Scopus subject areas

  • Statistics and Probability
  • Statistics, Probability and Uncertainty


Dive into the research topics of 'Null Models and Community Detection in Multi-Layer Networks'. Together they form a unique fingerprint.

Cite this