title: Quantifying the effect of temporal resolution on time-varying networks.
abstract: Time-varying networks describe a wide array of systems whose constituents and interactions evolve over time. They are defined by an ordered stream of interactions between nodes, yet they are often represented in terms of a sequence of static networks, each aggregating all edges and nodes present in a time interval of size Δt. In this work we quantify the impact of an arbitrary Δt on the description of a dynamical process taking place upon a time-varying network. We focus on the elementary random walk, and put forth a simple mathematical framework that well describes the behavior observed on real datasets. The analytical description of the bias introduced by time integrating techniques represents a step forward in the correct characterization of dynamical processes on time-varying graphs.
authors.affiliation: School of Computer Science, Carnegie Mellon University, 5000 Forbes Avenue, Pittsburgh PA 15213, USA.
authors.forename: Bruno
authors.initials: B
authors.lastname: Ribeiro
authors.forename: Nicola
authors.initials: N
authors.lastname: Perra
authors.forename: Andrea
authors.initials: A
authors.lastname: Baronchelli