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Detecting the Community Structure and Activity Patterns of Temporal Networks: A Non-Negative Tensor Factorization Approach
TLDR
We investigate the use of a latent factor decomposition technique, non-negative tensor factorization, to extract the community-activity structure of temporal networks. Expand
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Phase diagram of a Schelling segregation model
The collective behavior in a variant of Schelling’s segregation model is characterized with methods borrowed from statistical physics, in a context where their relevance was not conspicuous. AExpand
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COVID-19 outbreak response: a first assessment of mobility changes in Italy following national lockdown
Italy is currently experiencing the largest COVID-19 outbreak in Europe so far, with more than 100,000 confirmed cases. Following the identification of the first infections, on February 21, 2020,Expand
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Schelling segregation in an open city: a kinetically constrained Blume-Emery-Griffiths spin-1 system.
In the 70s Schelling introduced a multiagent model to describe the segregation dynamics that may occur with individuals having only weak preferences for "similar" neighbors. Recently variants of thisExpand
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Gender gaps in urban mobility
TLDR
We study urban mobility from a gendered perspective, combining commercial and open datasets for the city of Santiago, Chile. Expand
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COVID-19 outbreak response, a dataset to assess mobility changes in Italy following national lockdown
Italy has been severely affected by the COVID-19 pandemic, reporting the highest death toll in Europe as of April 2020. Following the identification of the first infections, on February 21, 2020,Expand
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Randomized reference models for temporal networks
TLDR
We propose a unified framework for classifying and understanding microcanonical RRMs (MRRMs) that sample networks with uniform probability. Expand
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Predicting City Poverty Using Satellite Imagery
TLDR
We apply a machine learning approach to the metropolitan areas of five different cities in North and South America, starting from pre-trained convolutional models used for poverty mapping in developing regions. Expand
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Fingerprinting temporal networks of close-range human proximity
TLDR
We show that simple dynamical processes computed over the time-varying proximity networks can uncover important features of the interaction patterns that go beyond standard statistical indicators of heterogeneity and burstiness, and can tell apart datasets that would otherwise look statistically similar. Expand
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Wearable Proximity Sensors for Monitoring a Mass Casualty Incident Exercise: Feasibility Study
Background Over the past several decades, naturally occurring and man-made mass casualty incidents (MCIs) have increased in frequency and number worldwide. To test the impact of such events onExpand
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