|
Abstract:
|
Multilayer networks provide a useful way to capture and model multiple relationships among objects. In this talk, I will introduce a community detection procedure that identifies densely connected vertex-layer sets in multilayer networks with heterogeneous community structure. A local modularity score is used to assess the significance of extracted communities. I will explore the utility of Multilayer Extraction through studies on social, transportation, and co-authorship multilayer networks. Furthermore, I will discuss the statistical properties of Multilayer Extraction and show consistency of identified communities in both the large graph and large number of layer regimes under the multilayer stochastic block model.
|
