Tuesday, November 03, 2020

Integrating Social Networks into Large-scale Urban Simulations

Building on past posts about our work with respect to generating large scale synthetic populations for agent-based models, we have a new paper entitled "Integrating Social Networks into Large-scale Urban Simulations for Disaster Responses" that was accepted at the 3rd ACM SIGSPATIAL International Workshop on GeoSpatial Simulation. In the paper we discuss our method to create synthetic populations  which incorporates social networks to generate for the New York megacity region. To demonstrate the utility of our approach, we use the generated synthetic population to initialize an agent-based model which not only generates basic patterns of life (e.g., commuting to and from work), but also allows us to explore how people react to disasters and how their social networks are changed by such events. 

If sounds of interest to you, below we provide the abstract to the paper, along with our synthetic population workflow and some sample outcomes from the model. At the bottom of the post we provide the full reference and link to the paper (the paper itself also links to a GitHub repository where more information about the synesthetic population can be found).

ABSTRACT: Social connections between people influence how they behave and where they go; however, such networks are rarely incorporated in agent-based models of disaster. To address this, we introduce a novel synthetic population method which specifically creates social relationships. This synthetic population is then used to instantiate a geographically explicit agent-based model for the New York megacity region which captures pre- and post- disaster behaviors. We demonstrate not only how social networks can be incorporated into models of disaster but also how such networks can impact decision making, opening up a variety of new application areas where network structures matter in urban settings. 

KEYWORDS: Urban Simulation, Agent-based models, Synthetic Populations, Social Networks, Geographical Information Systems, Disasters.

Synthetic population and social network generation workflow.
Synthetic population at household level within a census track (A) and social network of one individual (B).
Example of a heat-map of traffic density (A) Manhattan is center of the plot. The impact area of the disaster and the health status of the agents (B).

Full Reference:

Jiang, N., Burger, A., Crooks, A.T. and Kennedy, W.G. (2020), Integrating Social Networks into Large-scale Urban Simulations for Disaster Responses. Geosim ’20: 3rd ACM SIGSPATIAL International Workshop on GeoSpatial Simulation, Seattle, WA. (pdf)