The Intrinsic Scale of Networks is Small.

ASONAM '19: International Conference on Advances in Social Networks Analysis and Mining Vancouver British Columbia Canada August, 2019(2019)

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摘要
We define the intrinsic scale at which a network begins to reveal its identity as the scale at which subgraphs in the network (created by a random walk) are distinguishable from similar sized subgraphs in a perturbed copy of the network. We conduct an extensive study of intrinsic scale for several networks, ranging from structured (e.g. road networks) to ad-hoc and unstructured (e.g. crowd sourced information networks), to biological. We find: (a) The intrinsic scale is surprisingly small (7-20 vertices), even though the networks are many orders of magnitude larger. (b) The intrinsic scale quantifies "structure" in a network - networks which are explicitly constructed for specific tasks have smaller intrinsic scale. (c) The structure at different scales can be fragile (easy to disrupt) or robust.
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关键词
structure, signature, deep learning, convolutional neural networks
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