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Reachability problems for sequential dynamical systems with threshold functions
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A first-principles approach to understanding the internet's router-level topology
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Mobile call graphs: beyond power-law and lognormal distributions
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Patterns of influence in a recommendation network
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Clustering method incorporating network topology and dynamics
SpringSim '10 Proceedings of the 2010 Spring Simulation Multiconference
SUPE-Net: An Efficient Parallel Simulation Environment for Large-Scale Networked Social Dynamics
GREENCOM-CPSCOM '10 Proceedings of the 2010 IEEE/ACM Int'l Conference on Green Computing and Communications & Int'l Conference on Cyber, Physical and Social Computing
SBP'11 Proceedings of the 4th international conference on Social computing, behavioral-cultural modeling and prediction
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High performance informatics for pandemic preparedness
Proceedings of the Winter Simulation Conference
Modeling cellular network traffic with mobile call graph constraints
Proceedings of the Winter Simulation Conference
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We describe "first principles" based methods for developing synthetic urban and national scale social contact networks. Unlike simple random graph techniques, these methods use real world data sources and combine them with behavioral and social theories to synthesize networks. We develop a synthetic population for the United States modeling every individual in the population including household structure, demographics and a 24-hour activity sequence. The process involves collecting and manipulating public and proprietary data sets integrated into a common architecture for data exchange and then using these data sets to generate new relations. A social contact network is derived from the synthetic population based on physical co-location of interacting persons. We use graph measures to compare and contrast the structural characteristics of the social networks that span different urban regions. We then simulate diffusion processes on these networks and analyze similarities and differences in the structure of the networks.