UMR 5672

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Soutenance de Jordan Cambe

Understanding the complex dynamics of social systems with diverse formal tools
When Sep 26, 2019
from 11:00 AM to 01:00 PM
Where Salle R117 (Monod)
Attendees Jordan Cambe
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For the past two decades, electronic devices have revolutionized the traceability of social phenomena. Social dynamics now leave numerical footprints, which can be analyzed to better understand collective behaviors. The development of large online social networks (like Facebook, Twitter and more generally mobile communications) and connected physical structures (like transportation networks and geolocalised social platforms) resulted in the emergence of large longitudinal datasets. These new datasets bring the opportunity to develop new methods to analyze temporal dynamics in and of these systems.

The purpose of this PhD has been to explore the dynamics of social systems using three sets of tools: network science, statistical physics modeling and machine learning. During my defence, I will talk about 2 of my PhD projects: the study the behavior evolution of bike sharing system users (Vélo'v) and the study of cooperation/competition relations between stores. The topics covered will deal with temporal dynamics, users segmentation, complex networks, machine learning and the impact of new stores on established ones.