Detection of anomalous spatio-temporal patterns of app traffic in response to catastrophic events

Detection of anomalous spatio-temporal patterns of app traffic in response to catastrophic events

Abstract In this work, we uncover patterns of usage mobile phone applications and information spread in response to perturbations caused by unprecedented events. We focus on categorizing patterns of response in both space and time, tracking their relaxation over time. To this end, we use the NetMob2...

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Bibliographic Details
Main Authors: Sofia Medina, Shazia’Ayn Babul, Timothy LaRock, Rohit Sahasrabuddhe, Renaud Lambiotte, Nicola Pedreschi
Format: Article
Language:English
Published: SpringerOpen 2025-05-01
Series:EPJ Data Science
Subjects:
Data visualization
Mobile applications
Event detection
Disaster response
Urban mobility
Computational social science
Online Access:https://doi.org/10.1140/epjds/s13688-025-00546-w
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https://doi.org/10.1140/epjds/s13688-025-00546-w

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