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Titlebook: Complex Networks XI; Proceedings of the 1 Hugo Barbosa,Jesus Gomez-Gardenes,Marcos Oliveira Conference proceedings 2020 The Editor(s) (if a

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The Arf-Kervaire Invariant via ,ixed size and are sparse. This condition on the parameters of the network models mentioned above is both sufficient for consistent community recovery using our methods and also necessary to have any consistent community detection procedure. We also give some simulation results to demonstrate the efficacy of the proposed methods.
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Power of Nodes Based on Their Interdependenceuence. Second, we present several models that transform information about direct influence to a single vector with respect to the network structure. Finally, we compare our models with centrality measures on artificial and real networks.
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Consistent Recovery of Communities from Sparse Multi-relational Networks: A Scalable Algorithm with ixed size and are sparse. This condition on the parameters of the network models mentioned above is both sufficient for consistent community recovery using our methods and also necessary to have any consistent community detection procedure. We also give some simulation results to demonstrate the efficacy of the proposed methods.
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Zealotry and Influence Maximization in the Voter Model: When to Target Partial Zealots?trategies give higher allocations to normal agents, with some residual allocations to partial zealots, and allocations to both types of agents decrease with node degree. Our results emphasize that heterogeneity in agent properties strongly affects strategies for influence maximization on heterogeneous networks.
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Indications for Stable Fixationes, we propose an algorithm to calculate the number and the entropy of spanning trees of these networks by using the electrically equivalent transformations. The result allows us to evaluate the robustness and the homogeneity of their structure. The proposed technique is efficient and more general compared to the classical ones.
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