Flow of temporal network properties under local aggregation and time shuffling: a tool for characterizing, comparing and classifying temporal networks

Abstract

Although many tools have been developed and employed to characterize temporal networks, the issue of how to compare them remains largely open. It depends indeed on what features are considered as relevant, and on the way the differences in these features are quantified. In this paper, we propose to characterize temporal networks through their behaviour under general transformations that are local in time: (i) a local time shuffling, which destroys correlations at time scales smaller than a given scale $b$, while preserving large time scales, and (ii) a local temporal aggregation on time windows of length $n$. By varying $b$ and $n$, we obtain a flow of temporal networks, and flows of observable values, which encode the phenomenology of the temporal network on multiple time scales. We use a symbolic approach to summarize these flows into labels (strings of characters) describing their trends. These labels can then be used to compare temporal networks, validate models, or identify groups of networks with similar labels. Our procedure can be applied to any temporal network and with an arbitrary set of observables, and we illustrate it on an ensemble of data sets describing face-to-face interactions in various contexts, including both empirical and synthetic data.

References in corpus (40)

• Power-law distributions in empirical data
• Novel type of phase transition in a system of self-driven particles
• Temporal Networks
• Networks beyond pairwise interactions: structure and dynamics
• High-resolution measurements of face-to-face contact patterns in a primary school
• Dynamics of person-to-person interactions from distributed RFID sensor networks
• High resolution dynamical mapping of social interactions with active RFID
• Activity driven modeling of time varying networks
• Modern temporal network theory: A colloquium
• Contact patterns in a high school: a comparison between data collected using wearable sensors, contact diaries and friendship surveys
• The fundamental advantages of temporal networks
• Estimating Potential Infection Transmission Routes in Hospital Wards Using Wearable Proximity Sensors
• Path lengths, correlations, and centrality in temporal networks
• Contact patterns among high school students
• Causality-Driven Slow-Down and Speed-Up of Diffusion in Non-Markovian Temporal Networks
• Active Brownian Particles and Run-and-Tumble Particles: a Comparative Study
• Temporal motifs in time-dependent networks
• Graph Metrics for Temporal Networks
• Can co-location be used as a proxy for face-to-face contacts?
• Mitigation of infectious disease at school: targeted class closure vs school closure
• Data on face-to-face contacts in an office building suggests a low-cost vaccination strategy based on community linkers
• Temporal networks: slowing down diffusion by long lasting interactions
• Analytical computation of the epidemic threshold on temporal networks
• Scale-free Networks Well Done
• Social network dynamics of face-to-face interactions
• Betweenness Preference: Quantifying Correlations in the Topological Dynamics of Temporal Networks
• Effects of time window size and placement on the structure of aggregated networks
• An information-theoretic, all-scales approach to comparing networks
• How memory generates heterogeneous dynamics in temporal networks
• Detecting sequences of system states in temporal networks
• Randomized reference models for temporal networks
• From calls to communities: a model for time varying social networks
• Network comparison and the within-ensemble graph distance
• Detecting social (in)stability in primates from their temporal co-presence network
• The Temporal Rich Club Phenomenon
• From temporal network data to the dynamics of social relationships
• Time series analysis of temporal networks
• Modeling framework unifying contact and social networks
• Detecting periodic time scales in temporal networks
• Simple crowd dynamics to generate complex temporal contact networks

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