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Percolation on feature-enriched interconnected systems

Oriol Artime, Manlio De Domenico

2021Nature Communications30 citationsDOIOpen Access PDF

Abstract

Percolation is an emblematic model to assess the robustness of interconnected systems when some of their components are corrupted. It is usually investigated in simple scenarios, such as the removal of the system's units in random order, or sequentially ordered by specific topological descriptors. However, in the vast majority of empirical applications, it is required to dismantle the network following more sophisticated protocols, for instance, by combining topological properties and non-topological node metadata. We propose a novel mathematical framework to fill this gap: networks are enriched with features and their nodes are removed according to the importance in the feature space. We consider features of different nature, from ones related to the network construction to ones related to dynamical processes such as epidemic spreading. Our framework not only provides a natural generalization of percolation but, more importantly, offers an accurate way to test the robustness of networks in realistic scenarios.

Topics & Concepts

Robustness (evolution)Computer scienceGeneralizationPercolation (cognitive psychology)Topology (electrical circuits)Complex networkInterdependent networksGiant componentNetwork topologyStatistical physicsPercolation theorySimple (philosophy)Percolation thresholdNetwork structureDynamical systems theoryTheoretical computer scienceFeature (linguistics)Node (physics)Complex systemBiological networkNetwork modelMathematicsArtificial neural networkComplex Network Analysis TechniquesOpportunistic and Delay-Tolerant NetworksOpinion Dynamics and Social Influence
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