Hyperbolic mapping of human proximity networks.

ABSTRACT: Human proximity networks are temporal networks representing the close-range proximity among humans in a physical space. They have been extensively studied in the past 15 years as they are critical for understanding the spreading of diseases and information among humans. Here we address the problem of mapping human proximity networks into hyperbolic spaces. Each snapshot of these networks is often very sparse, consisting of a small number of interacting (i.e., non-zero degree) nodes. Yet, we show that the time-aggregated representation of such systems over sufficiently large periods can be meaningfully embedded into the hyperbolic space, using methods developed for traditional (non-mobile) complex networks. We justify this compatibility theoretically and validate it experimentally. We produ

SUBMITTER: Rodriguez-Flores MA 

PROVIDER: S-EPMC7679465 | biostudies-literature | 2020 Nov

REPOSITORIES: biostudies-literature