# Scale-free properties of weighted networks with connectivity-driven topology

@article{Jeewski2005ScalefreePO, title={Scale-free properties of weighted networks with connectivity-driven topology}, author={Wojciech Jeżewski}, journal={Physica A-statistical Mechanics and Its Applications}, year={2005}, volume={354}, pages={672-680} }

## 13 Citations

### PROPERTIES OF WEIGHTED COMPLEX NETWORKS

- Computer Science
- 2005

This work studied two kinds of weighted networks, weighted small-world (WSW) and weighted scale-free (WSF), and the epidemic spreading process in both weighted networks was studied based on the standard susceptible-infected (SI) model.

### Evolving model of weighted networks inspired by scientific collaboration networks

- Computer Science
- 2005

### A Survey of Evolving Models for Weighted Complex Networks based on their Dynamics and Evolution

- Computer ScienceArXiv
- 2020

This chapter discusses the evolution of weighted networks and evolving models to generate different types of synthetic weighted networks, including undirected, directed, signed, multilayered, community, and core-periphery structured weighted networks.

### Evolving Models for Dynamic Weighted Complex Networks

- Computer SciencePrinciples of Social Networking
- 2021

This chapter will cover the evolution of weighted complex networks and evolving models to generate different types of synthetic weighted networks, including undirected, directed, signed, multilayered, community, and core–periphery structured weighted networks.

### Construction of bipartite and unipartite weighted networks from collections of journal papers

- Computer Science
- 2005

This work presents a model that allows the study of research specialties through the manifestations of the specialty's social and epistemological processes in a collection of journal papers.…

### Modelling disease spread and control in networks: implications for plant sciences.

- BiologyThe New phytologist
- 2007

A growing number of empirical applications of network theory in human medicine and animal disease ecology confirm the potential of the approach, and suggest that network thinking could also benefit plant epidemiology and forest pathology, particularly in human-modified pathosystems linked by commercial transport of plant and disease propagules.

### Effect of long-range interactions on nanoparticle-induced aggregation.

- ChemistryPhysical chemistry chemical physics : PCCP
- 2016

Surprisingly, the evolution of aggregating systems toward more significant inhomogeneity takes place when the interaction strength is initially large and increases fast enough with the size of aggregates.

### Kinetics of aggregation in liquids with dispersed nanoparticles.

- PhysicsPhysical chemistry chemical physics : PCCP
- 2015

It is shown that, depending on a specific functional form of the growth rate, the size distribution of aggregates can display very different shapes, including various multimodal structures.

## References

SHOWING 1-10 OF 45 REFERENCES

### Highly clustered scale-free networks.

- Computer SciencePhysical review. E, Statistical, nonlinear, and soft matter physics
- 2002

The model shows stylized features of real-world networks: power-law distribution of degree, linear preferential attachment of new links, and a negative correlation between the age of a node and its link attachment rate.

### Pseudofractal scale-free web.

- MathematicsPhysical review. E, Statistical, nonlinear, and soft matter physics
- 2002

It is found that scale-free random networks are excellently modeled by simple deterministic graphs and exactly and numerically with high precision all main characteristics of the graph are found.

### Weighted evolving networks: coupling topology and weight dynamics.

- MathematicsPhysical review letters
- 2004

A model for the growth of weighted networks that couples the establishment of new edges and vertices and the weights' dynamical evolution and yields a nontrivial time evolution of vertices' properties and scale-free behavior for the weight, strength, and degree distributions.

### Organization of growing random networks.

- Computer SciencePhysical review. E, Statistical, nonlinear, and soft matter physics
- 2001

The organizational development of growing random networks is investigated, and the combined age and degree distribution of nodes shows that old nodes typically have a large degree.

### Stationary and nonstationary properties of evolving networks with preferential linkage.

- Computer SciencePhysical review. E, Statistical, nonlinear, and soft matter physics
- 2002

It is argued that nonstationary effects are not unlikely in real networks, although these effects may not be apparent, especially in networks with a slowly varying mean degree.

### Emergence of scaling in random networks

- Computer ScienceScience
- 1999

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.

### Connectivity of growing random networks.

- MathematicsPhysical review letters
- 2000

A solution for the time- and age-dependent connectivity distribution of a growing random network is presented and the power law N(k) approximately k(-nu) is found, where the exponent nu can be tuned to any value in the range 2.

### Evolution of networks with aging of sites

- MathematicsPhysical review. E, Statistical physics, plasmas, fluids, and related interdisciplinary topics
- 2000

It is found both from simulation and analytically that the network shows scaling behavior only in the region alpha<1, when alpha increases from -infinity to 0, and the exponent gamma of the distribution of connectivities grows from 2 to the value for the network without aging.