Generation of Reusable Synthetic Population and Social Networks

Building on our work on synthetic populations, Na (Richard) Jiang, Bill Kennedy, Hamdi Kavak, and myself have a new paper which was presented at the 2021 Annual Modeling and Simulation (ANNSIM) Conference entitled "Generation of Reusable Synthetic Population And Social Networks for Agent-Based Modeling." Rather than go into details about the paper, below is the abstract and as the conference was virtual, the presentation which accompanies the paper was prerecorded by Richard and is embedded below. If you want to find out more, at the bottom of the post there is a link to a draft of the paper.

Abstract: Within agent-based models, agents interact with each other (e.g., 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 networks. To overcome this challenge, this paper introduces a new 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 and to highlight the role of social networks, 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 modeling problems. 

Keywords: Synthetic Population, Agent-Based Modeling, New York, Traffic Dynamics, Disease Models.

  Full Reference: 

Jiang, N., Crooks, A.T., Kennedy, W.G., and Kavak, H. (2021), Generation of Reusable Synthetic Population And Social Networks for Agent-Based Modeling, 2021 Annual Modeling and Simulation Conference (ANNSIM). (pdf)