The hidden dependence of spreading vulnerability on topological complexity


Abstract in English

Many dynamical phenomena, e.g., pathogen transmission, disruptions in transport over networks, and (fake) news purveyance, concern spreading that plays out on top of networks with changing architectures over time - commonly known as temporal networks. Assessing a systems proneness to facilitate spreading phenomena, which we refer to as its spreading vulnerability, from its topological information alone remains a challenging task. We report a methodological advance in terms of a novel metric for topological complexity: entanglement entropy. Using publicly available datasets, we demonstrate that the metric naturally allows for topological comparisons across vastly different systems, and importantly, reveals that the spreading vulnerability of a system can be quantitatively related to its topological complexity. In doing so, the metric opens itself for applications in a wide variety of natural, social, biological and engineered systems.

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