We develop a simple theoretical framework for the evolution of weighted network that is consistent with a number of stylized features of real-world data. In our framework, the Barabasi-Albert model of network evolution is extended as recently proposed by Stanley and colleagues in their work on complex system dynamics . Our model is verify by means of simulations and real world trade data. We show that the model correctly predicts the intensity and growth distribution of links, the size-variance relationships of the growth of link values , the relationship between the degree and strength of nodes, as well as the scale-free structure of the network.
We develop a simple theoretical framework for the evolution of weighted networks that is consistent with a number of stylized features of real-world data. In our framework, the Barabasi-Albert model of network evolution is extended by assuming that link weights evolve according to a geometric Brownian motion . Our model is verified by means of simulations and real world trade data. We show that the model correctly predicts the intensity and growth distribution of links, the size-variance relationships of the growth of link weights , the relationship between the degree and strength of nodes, as well as the scale-free structure of the network.
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network
networks
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as recently proposed by Stanley and colleagues in their work on complex system dynamics
by assuming that link weights evolve according to a geometric Brownian motion
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verify
verified
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values
weights