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DYSONET in a glance

Develop the basic science of complex social networks in a quantitative way

Apply our findings to the dynamics of human behavior, and generalize to a wider range of networks, including economic, traffic, and environmental networks.

Methods and techniques based on Statistical Physics concepts

Quantitative characterization of complex social networks by analyzing a number of real-world phenomena, including: crowd behavior, search strategies, traffic flow, dynamics of human relationship networks, spread of epidemics

Dynamic patterns in other disciplines, such as Economics and Finance, and Environmental networks.

Characterize, optimize and control the structure, dynamics and flow in complex social networks

Our studies will use extensive real-world data of social nature, which will be collected in the frame of the project.

(c) Computational Physics Group A.U.Th.