Circuits as a Classifier for Small-World Network Models

13 years 2 months ago

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The number and length distribution of circuits or loops in a graph or network give important insights into its key characteristics. We discuss the circuit properties of various small-world or scale-free network models generated with different small-world probability parameter values. The small-world properties usually manifest themselves in terms of reduced path-length properties or the set of inter-node distances present in a graph. We show how the number of circuits present can increase or decrease with a larger probability of small-world shortcut links applied, depending upon which model is used. Circuit properties are computationally expensive and we consider counting only a partial circuit distribution and thus being able to use circuits as a classifier for these models in practical cases.

Arno Leist, Kenneth A. Hawick

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