Construction of Directed Assortative Configuration Graphs
Philippe Deprez, Mario V. W\"uthrich

TL;DR
This paper presents an explicit algorithm for constructing directed assortative configuration graphs that incorporate a specified degree distribution and desired level of assortativity, addressing limitations of previous models.
Contribution
It introduces a novel algorithm enabling the creation of directed graphs with controlled assortativity based on a given bi-degree distribution.
Findings
Algorithm successfully constructs graphs with specified assortativity.
Graphs reflect realistic network properties like degree correlations.
Method extends existing models to include assortative mixing.
Abstract
Constructions of directed configuration graphs based on a given bi-degree distribution were introduced in random graph theory some years ago. These constructions lead to graphs where the degrees of two nodes belonging to the same edge are independent. However, it is observed that many real-life networks are assortative, meaning that edges tend to connect low degree nodes with high degree nodes, or variations thereof. In this article we provide an explicit algorithm to construct directed assortative configuration graphs based on a given bi-degree distribution and an arbitrary pre-specified assortativity.
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