We study a recent model of random networks based on the presence of an intrinsic character of the vertices called fitness. The vertex fitnesses are drawn from a given probability distribution density. The edges between pairs of vertices are drawn according to a linking probability function depending on the fitnesses of the two vertices involved. We study here different choices for the probability distribution densities and the linking functions. We find that, irrespective of the particular choices, the generation of scale-free networks is straight- forward. We then derive the general conditions under which scale-free behavior appears. This model could then represent a possible explanation for the ubiquity and robustness of such structures
A growing family of random graphs is called robust if it retains a giant component after percolation...
<div><p>In real networks, the resources that make up the nodes and edges are finite. This constraint...
In this work we study a simple evolutionary model of bipartite networks whose evolution is based on ...
We study a recent model of random networks based on the presence of an intrinsic character of the ve...
A new mechanism leading to scale-free networks is proposed in this Letter. It is shown that, in many...
A new mechanism leading to scale-free networks is proposed in this Letter. It is shown that, in many...
AbstractWe propose a new mechanism leading to scale-free networks which is based on the presence of ...
A new mechanism leading to scale-free networks is proposed in this Letter. It is shown that, in many...
We show how scale-free degree distributions can emerge naturally from growing networks by using rand...
In many networks, the link between any pair of vertices conforms to a specific probability, such as ...
In this paper, we present a simple model of scale-free networks that incorporates both preferential ...
The concept of scale-free networks has been widely applied across natural and physical sciences. Man...
Uncorrelated random scale-free networks are useful null models to check the accuracy and the analyti...
A random graph evolution mechanism is defined. The evolution studied is a combination of the prefere...
In real networks, the resources that make up the nodes and edges are finite. This constraint poses a...
A growing family of random graphs is called robust if it retains a giant component after percolation...
<div><p>In real networks, the resources that make up the nodes and edges are finite. This constraint...
In this work we study a simple evolutionary model of bipartite networks whose evolution is based on ...
We study a recent model of random networks based on the presence of an intrinsic character of the ve...
A new mechanism leading to scale-free networks is proposed in this Letter. It is shown that, in many...
A new mechanism leading to scale-free networks is proposed in this Letter. It is shown that, in many...
AbstractWe propose a new mechanism leading to scale-free networks which is based on the presence of ...
A new mechanism leading to scale-free networks is proposed in this Letter. It is shown that, in many...
We show how scale-free degree distributions can emerge naturally from growing networks by using rand...
In many networks, the link between any pair of vertices conforms to a specific probability, such as ...
In this paper, we present a simple model of scale-free networks that incorporates both preferential ...
The concept of scale-free networks has been widely applied across natural and physical sciences. Man...
Uncorrelated random scale-free networks are useful null models to check the accuracy and the analyti...
A random graph evolution mechanism is defined. The evolution studied is a combination of the prefere...
In real networks, the resources that make up the nodes and edges are finite. This constraint poses a...
A growing family of random graphs is called robust if it retains a giant component after percolation...
<div><p>In real networks, the resources that make up the nodes and edges are finite. This constraint...
In this work we study a simple evolutionary model of bipartite networks whose evolution is based on ...