Fitness-Based Growth of Directed Networks with Hierarchy
Niall Rodgers, Peter Tino, Samuel Johnson

TL;DR
This paper introduces a simple growing network model combining degree-based preferential attachment and node fitness to explain the emergence of hierarchy and directionality in directed networks, aligning with real-world network features.
Contribution
It presents a novel model that links network growth mechanisms with hierarchy and directionality, demonstrating how these features can coexist and be predicted by fitness parameters.
Findings
Preferential attachment can induce hierarchy in networks.
Scale-free degree distributions can coexist with hierarchy.
Node fitness correlates with trophic level and predicts network incoherence.
Abstract
Growing attention has been brought to the fact that many real directed networks exhibit hierarchy and directionality as measured through techniques like Trophic Analysis and non-normality. We propose a simple growing network model where the probability of connecting to a node is defined by a preferential attachment mechanism based on degree and the difference in fitness between nodes. In particular, we show how mechanisms such as degree-based preferential attachment and node fitness interactions can lead to the emergence of the spectrum of hierarchy and directionality observed in real networks. In this work, we study various features of this model relating to network hierarchy, as measured by Trophic Analysis. This includes (I) how preferential attachment can lead to network hierarchy, (II) how scale-free degree distributions and network hierarchy can coexist, (III) the correlation…
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Taxonomy
TopicsGame Theory and Applications
