Hierarchical route to the emergence of leader nodes in real-world networks

@article{OBrien2020HierarchicalRT,
  title={Hierarchical route to the emergence of leader nodes in real-world networks},
  author={Joseph D. O’Brien and K. Oliveira and J. Gleeson and Malbor Asllani},
  journal={arXiv: Physics and Society},
  year={2020}
}
A large number of complex systems, naturally emerging in various domains, are well described by directed networks, resulting in numerous interesting features that are absent from their undirected counterparts. Among these properties is a strong non-normality, inherited by a strong asymmetry that characterizes such systems and guides their underlying hierarchy. In this work, we consider an extensive collection of empirical networks and analyze their structural properties using information… Expand

Figures from this paper

References

SHOWING 1-10 OF 91 REFERENCES
Emergence of hierarchy in networked endorsement dynamics
TLDR
A generative model for the dynamics of hierarchies using time-varying networks, in which new links are formed based on the preferences of nodes in the current network and old links are forgotten over time is introduced. Expand
Patterns of non-normality in networked systems.
TLDR
Non-normality promotes the emergence of patterns in cases where a classical linear analysis would not predict them, and relies on the fact that non-normal networks are pervasively found, motivating the general interest of the mechanism here discussed. Expand
Complex networks: Structure and dynamics
Coupled biological and chemical systems, neural networks, social interacting species, the Internet and the World Wide Web, are only a few examples of systems composed by a large number of highlyExpand
Detecting rich-club ordering in complex networks
Uncovering the hidden regularities and organizational principles of networks arising in physical systems ranging from the molecular level to the scale of large communication infrastructures is theExpand
Collective dynamics of ‘small-world’ networks
TLDR
Simple models of networks that can be tuned through this middle ground: regular networks ‘rewired’ to introduce increasing amounts of disorder are explored, finding that these systems can be highly clustered, like regular lattices, yet have small characteristic path lengths, like random graphs. Expand
Structure and dynamical behavior of non-normal networks
TLDR
A collection of empirical networks in a wide spectrum of disciplines are analyzed and it is shown that strong non-normality is ubiquitous in network science. Expand
Emergence of scaling in random networks
TLDR
A model based on these two ingredients reproduces the observed stationary scale-free distributions, which indicates that the development of large networks is governed by robust self-organizing phenomena that go beyond the particulars of the individual systems. Expand
Resilience for stochastic systems interacting via a quasi-degenerate network.
TLDR
Non-normality and quasidegenerate networks may, therefore, amplify the inherent stochasticity and so contribute to altering the perception of resilience, as quantified via conventional deterministic methods. Expand
Efficient communication over complex dynamical networks: The role of matrix non-normality.
TLDR
A framework that enables us to examine how network structure, noise, and interference between consecutive packets jointly determine transmission performance in complex networks governed by linear dynamics is developed. Expand
Spatio-temporal networks: reachability, centrality and robustness
TLDR
A model of spatio-temporal paths in time-varying spatially embedded networks which captures the property that, as in many real-world systems, interaction between nodes is non-instantaneous and governed by the space in which they are embedded is proposed. Expand
...
1
2
3
4
5
...