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The degree distribution of the dependence network is obviously different from the original friendship network ((alpha=1)).
For a given friendship network, we construct a dependence network by removing the insignificant edges based on statistical validation [41].
For each society, we set a significant level α and remove those insignificant links, resulting a directed dependence network.
For each society, we construct a dependence network of individuals, which only keeps the multiscale backbone of original friendship network (see construction of dependence network in Section 2). Figure 1 illustrates the dependence network from a virtual society and some basic statistics about the topological structure.
For a given dependence network, we can estimate a position ratio profile for each individual (see quantifying position ratio profile in Section 2).
Figure 1(A), (B), (C) show the topological structure of the dependence network constructed from a virtual society with significant level (alpha=0.01, 0.05, 0.1), respectively.
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By the disparity filter [41], the dependence networks are the backbones of the original friendship networks.
Figure 1 Illustration of dependence networks and basic statistics of network structure.
We use a statistical filtering method to construct dependence networks from weighted friendship networks of individuals.
(E) In-degree distribution (P k_{mathrm{in}})) of the dependence networks in (A) (B) (C).
(D) Out-degree distribution (P k_{mathrm{out}})) of the dependence networks in (A) (B) (C).
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