Integrating social networks into large-scale urban simulations for disaster responses

Na Jiang; Annetta Burger; Andrew T. Crooks; William G. Kennedy

doi:10.1145/3423335.3428168

Integrating social networks into large-scale urban simulations for disaster responses

Na Jiang, Annetta Burger, Andrew T. Crooks, William G. Kennedy

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

4 Scopus citations

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
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	https://doi.org/10.1145/3423335.3428168
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

Conference

Conference	3rd ACM SIGSPATIAL International Workshop on GeoSpatial Simulation, GeoSim 2020
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.

Funders	Funder number
Defense Technology Research Agency	HDTRA1-16-0043
George Mason University

Keywords

agent-based models
disasters
geographical information systems
social networks
synthetic populations
urban simulation

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

Access to Document

10.1145/3423335.3428168

Cite this

Jiang, N., Burger, A., Crooks, A. T., & Kennedy, W. G. (2020). Integrating social networks into large-scale urban simulations for disaster responses. In T. Anderson, J.-S. Kim, & A. Shashidharan (Eds.), Proceedings of the 3rd ACM SIGSPATIAL International Workshop on GeoSpatial Simulation, GeoSim 2020 (pp. 52-55). (Proceedings of the 3rd ACM SIGSPATIAL International Workshop on GeoSpatial Simulation, GeoSim 2020). Association for Computing Machinery, Inc. https://doi.org/10.1145/3423335.3428168

Jiang, Na ; Burger, Annetta ; Crooks, Andrew T. et al. / Integrating social networks into large-scale urban simulations for disaster responses. Proceedings of the 3rd ACM SIGSPATIAL International Workshop on GeoSpatial Simulation, GeoSim 2020. editor / Taylor Anderson ; Joon-Seok Kim ; Ashwin Shashidharan. Association for Computing Machinery, Inc, 2020. pp. 52-55 (Proceedings of the 3rd ACM SIGSPATIAL International Workshop on GeoSpatial Simulation, GeoSim 2020).

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title = "Integrating social networks into large-scale urban simulations for disaster responses",

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.",

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author = "Na Jiang and Annetta Burger and Crooks, {Andrew T.} and Kennedy, {William G.}",

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doi = "10.1145/3423335.3428168",

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series = "Proceedings of the 3rd ACM SIGSPATIAL International Workshop on GeoSpatial Simulation, GeoSim 2020",

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Jiang, N, Burger, A, Crooks, AT & Kennedy, WG 2020, Integrating social networks into large-scale urban simulations for disaster responses. in T Anderson, J-S Kim & A Shashidharan (eds), Proceedings of the 3rd ACM SIGSPATIAL International Workshop on GeoSpatial Simulation, GeoSim 2020. Proceedings of the 3rd ACM SIGSPATIAL International Workshop on GeoSpatial Simulation, GeoSim 2020, Association for Computing Machinery, Inc, pp. 52-55, 3rd ACM SIGSPATIAL International Workshop on GeoSpatial Simulation, GeoSim 2020, Seattle, United States, 11/3/20. https://doi.org/10.1145/3423335.3428168

Integrating social networks into large-scale urban simulations for disaster responses. / Jiang, Na; Burger, Annetta; Crooks, Andrew T. et al.
Proceedings of the 3rd ACM SIGSPATIAL International Workshop on GeoSpatial Simulation, GeoSim 2020. ed. / Taylor Anderson; Joon-Seok Kim; Ashwin Shashidharan. Association for Computing Machinery, Inc, 2020. p. 52-55 (Proceedings of the 3rd ACM SIGSPATIAL International Workshop on GeoSpatial Simulation, GeoSim 2020).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

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AB - 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.

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Jiang N, Burger A, Crooks AT, Kennedy WG. Integrating social networks into large-scale urban simulations for disaster responses. In Anderson T, Kim JS, Shashidharan A, editors, Proceedings of the 3rd ACM SIGSPATIAL International Workshop on GeoSpatial Simulation, GeoSim 2020. Association for Computing Machinery, Inc. 2020. p. 52-55. (Proceedings of the 3rd ACM SIGSPATIAL International Workshop on GeoSpatial Simulation, GeoSim 2020). doi: 10.1145/3423335.3428168

Integrating social networks into large-scale urban simulations for disaster responses

Abstract

Publication series

Conference

Funding

Keywords

UN SDGs

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