Structure of complex networks: Quantifying edge-to-edge relations by failure-induced flow redistribution
Not on the map. Why?
Abstract (arXiv)
The analysis of complex networks has so far revolved mainly around the role of nodes and communities of nodes. However, the dynamics of interconnected systems is commonly focalised on edge processes, and a dual edge-centric perspective can often prove more natural. Here we present graph-theoretical measures to quantify edge-to-edge relations inspired by the notion of flow redistribution induced by edge failures. Our measures, which are related to the pseudo-inverse of the Laplacian of the network, are global and reveal the dynamical interplay between the edges of a network, including potentially non-local interactions. Our framework also allows us to define the embeddedness of an edge, a measure of how strongly an edge features in the weighted cuts of the network. We showcase the general applicability of our edge-centric framework through analyses of the Iberian Power grid, traffic flow in road networks, and the C. elegans neuronal network.
Key facts. Cited by 3 papers in the map (data through 7 Oct 2026). First posted on arXiv 25 Mar 2013.
Builds on
No reference list yet.
Built on by
Citing papers per year: 2022: 1; 2023: 2.
3 papers.
- 2022Simplicial Convolutional Filterscited by 18
- 2023Hodge-Compositional Edge Gaussian Processescited by 16
- 2023Disentangling the Spectral Properties of the Hodge Laplacian: Not All Small Eigenvalues Are Equalcited by 5
- 2023Disentangling the Spectral Properties of the Hodge Laplacian: Not All Small Eigenvalues Are Equal24 Nov 2023
- 2023Hodge-Compositional Edge Gaussian Processes30 Oct 2023
- 2022Simplicial Convolutional Filters27 Jan 2022