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Characterizing the Dynamical Importance of Network Nodes and Links
Open accessAbstract
The largest eigenvalue of the adjacency matrix of networks is a key quantity determining several important dynamical processes on complex networks. Based on this fact, we present a quantitative, objective characterization of the dynamical importance of network nodes and links in terms of their effect on the largest eigenvalue. We show how our characterization of the dynamical importance of nodes can be affected by degree-degree correlations and network community structure. We discuss how our characterization can be used to optimize techniques for controlling certain network dynamical processes and apply our results to real networks.
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Cites
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Metadata
- Authors
- Restrepo, J. G., Ott, E., & Hunt, B. R.
- Venue
- Physical Review Letters
- Publisher
- American Physical Society (APS)
- Published
- 2006-09-01
- Volume
- 97
- Issue
- 9
- Pages
- 094102-094102
- ISSN
- 0031-9007 (ISSN-L)
- 1079-7114
- OpenAlex
- W2078327425
- Cited by
- 260
- References
- 1
- FWCI
- 4.67
- Type
- journal article
- Language
- en
- Open access
- green
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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.
