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- A nd 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.
Original language | English |
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Title of host publication | Proceedings of the 3rd ACM SIGSPATIAL International Workshop on GeoSpatial Simulation, GeoSim 2020 |
Editors | Taylor Anderson, Joon-Seok Kim, Ashwin Shashidharan |
Publisher | Association for Computing Machinery, Inc |
Pages | 52-55 |
Number of pages | 4 |
ISBN (Electronic) | 9781450381611 |
DOIs | |
State | Published - Nov 3 2020 |
Externally published | Yes |
Event | 3rd ACM SIGSPATIAL International Workshop on GeoSpatial Simulation, GeoSim 2020 - Seattle, United States Duration: Nov 3 2020 → … |
Publication series
Name | Proceedings of the 3rd ACM SIGSPATIAL International Workshop on GeoSpatial Simulation, GeoSim 2020 |
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Conference
Conference | 3rd ACM SIGSPATIAL International Workshop on GeoSpatial Simulation, GeoSim 2020 |
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Country/Territory | United States |
City | Seattle |
Period | 11/3/20 → … |
Funding
This work was supported by the Center for Social Complexity at George Mason University and the Defense Technology Research Agency (DTRA) under Grant number HDTRA1-16-0043. The opinions, findings,and conclusions or recommendations expressed in this work are those of the authors and do not necessarily reflect the views of the sponsors.
Keywords
- agent-based models
- disasters
- geographical information systems
- social networks
- synthetic populations
- urban simulation