Complex Network Measurements: Estimating the Relevance of Observed Properties

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Executive Summary

Complex networks, modeled as large graphs, received much attention during these last years. However, data on such networks is only available through intricate measurement procedures. Until recently, most studies assumed that these procedures eventually lead to samples large enough to be representative of the whole, at least concerning some key properties. This has crucial impact on network modeling and simulation, which rely on these properties. Recent contributions proved that this approach may be misleading, but no solution has been proposed. The authors provide here the first practical way to distinguish between cases where it is indeed misleading, and cases where the observed properties may be trusted.

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