Characterizing cycle structure in complex networks
Not on the map. Why?
Abstract (arXiv)
Cycle is the simplest structure that brings redundant paths in network connectivity and feedback effects in network dynamics. Focusing on cycle structure, this paper defines a new matrix, named cycle number matrix, to represent cycle information of a network, and an index, named cycle ratio, to quantify the node importance. Experiments on real networks suggest that cycle ratio contains rich information in addition to well-known benchmark indices, for example, the node rankings by cycle ratio are largely different from rankings by degree, H-index, coreness, betweenness and articulation ranking, while the rankings by degree, H-index, coreness are very similar to each other. Extensive experiments on identifying vital nodes that maintain network connectivity, facilitate network synchronization and maximize the early reach of spreading show that cycle ratio is competitive to betweenness and overall better than other benchmarks. We believe the in-depth analyses on cycle structure may yield novel insights, metrics, models and algorithms for network science.
Key facts. Cited by 3 papers in the map (data through 14 Oct 2026). First posted on arXiv 22 Jan 2020.
Builds on
No reference list yet.
Built on by
Citing papers per year: 2023: 1; 2024: 2.
3 papers.
- 2024Hypergraph Attacks via Injecting Homogeneous Nodes into Elite Hyperedgescited by 4
- 2023Comprehensive Analysis of Network Robustness Evaluation Based on Convolutional Neural Networks with Spatial Pyramid Poolingcited by 1
- 2024A Quick Framework for Evaluating Worst Robustness of Complex Networkscited by 0
- 2024Hypergraph Attacks via Injecting Homogeneous Nodes into Elite Hyperedges24 Dec 2024
- 2024A Quick Framework for Evaluating Worst Robustness of Complex Networks28 Feb 2024
- 2023Comprehensive Analysis of Network Robustness Evaluation Based on Convolutional Neural Networks with Spatial Pyramid Pooling10 Aug 2023