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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.
Computer viruses are evolving by developing spreading mechanisms based on the use of multiple vectors of propagation. The use of the social network as an extra vector of attack to penetrate the security measures in IP networks is improving the effect
Social interactions are stratified in multiple contexts and are subject to complex temporal dynamics. The systematic study of these two features of social systems has started only very recently mainly thanks to the development of multiplex and time-v
We study SIS epidemic spreading processes unfolding on a recent generalisation of the activity-driven modelling framework. In this model of time-varying networks each node is described by two variables: activity and attractiveness. The first, describ
Online social media have greatly affected the way in which we communicate with each other. However, little is known about what are the fundamental mechanisms driving dynamical information flow in online social systems. Here, we introduce a generative
Background: Controlling global epidemics in the real world and accelerating information propagation in the artificial world are of great significance, which have activated an upsurge in the studies on networked spreading dynamics. Lots of efforts hav