Question 3

 A network G' is generated from a real network G. The following properties are observed:

  • G' preserves the exact degree sequence of G.
  • The clustering coefficient is close to that expected in a random graph with the same degree sequence.
  • The construction process depends explicitly on the original network structure.

Which method best explains these observations?

a) Configuration Model, because it generates networks with the same degree sequence and produces low clustering typical of random graphs.

b) Degree-Preserving Randomization, because it modifies the original network through edge swaps that preserve degrees while driving the network toward a random configuration.

c) Hidden-variable model, because it generates networks from probabilistic connections based on node attributes, rather than modifying the original network.

d) A deterministic graph construction, because preserving the degree sequence uniquely determines the network structure.

e) None of the above.

Original idea by George Gigilas Junior

Comentários

  1. Joao Meidanis4 de abril de 2026 às 06:22

    I find this question hard, because we haven't studied properties of random networks given a certain degree distribution.

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