Generation of Reusable Synthetic Population and Social Networks for Agent-Based Modeling

Authors: Na Jiang*, George Mason University, Annetta Burger, George Mason University, Andrew Crooks, The University at Buffalo
Topics: Spatial Analysis & Modeling, Urban Geography, Geography and Urban Health
Keywords: Synthetic Population, Agent-Based Modeling, New York, Traffic Dynamics, Disease Models
Session Type: Virtual Paper
Day: 4/7/2021
Start / End Time: 4:40 PM / 5:55 PM
Room: Virtual 41
Presentation File: No File Uploaded


Within agent-based models, agents interact with each other (via social networks) and their environment, and it is through such interactions more aggregate patterns emerge (e.g., disease outbreaks, traffic jams. While the popularity of agent-based modeling has grown, one challenge remains, that of creating and sharing realistic synthetic populations which incorporate social and physical networks. To overcome this challenge, this paper introduces a mixed method approach that creates a reusable synthetic population using the New York Metro Area as a study area. Our method directly incorporates social networks (i.e., connections within a family or workplace) when creating a synthetic population. To demonstrate the utility and reusability of the synthetic population dataset and to highlight the role of the social network we show two example applications: traffic dynamics and the spread of a disease. These applications demonstrate how our synthetic population method can be easily utilized for different purposes.

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