TY - JOUR
T1 - Space, time, and situational awareness in natural hazards
T2 - a case study of Hurricane Sandy with social media data
AU - Wang, Zheye
AU - Ye, Xinyue
N1 - Funding Information:
This work was supported by the National Science Foundation [1416509, 1637242].
Publisher Copyright:
© 2018, © 2018 Cartography and Geographic Information Society.
Copyright:
Copyright 2019 Elsevier B.V., All rights reserved.
PY - 2019/7/4
Y1 - 2019/7/4
N2 - Various methods have been developed to investigate the geospatial information, temporal component, and message content in disaster-related social media data to enrich human-centric information for situational awareness. However, few studies have simultaneously analyzed these three dimensions (i.e. space, time, and content). With an attempt to bring a space–time perspective into situational awareness, this study develops a novel approach to integrate space, time, and content dimensions in social media data and enable a space–time analysis of detailed social responses to a natural disaster. Using Markov transition probability matrix and location quotient, we analyzed the Hurricane Sandy tweets in New York City and explored how people’s conversational topics changed across space and over time. Our approach offers potential to facilitate efficient policy/decision-making and rapid response in mitigations of damages caused by natural disasters.
AB - Various methods have been developed to investigate the geospatial information, temporal component, and message content in disaster-related social media data to enrich human-centric information for situational awareness. However, few studies have simultaneously analyzed these three dimensions (i.e. space, time, and content). With an attempt to bring a space–time perspective into situational awareness, this study develops a novel approach to integrate space, time, and content dimensions in social media data and enable a space–time analysis of detailed social responses to a natural disaster. Using Markov transition probability matrix and location quotient, we analyzed the Hurricane Sandy tweets in New York City and explored how people’s conversational topics changed across space and over time. Our approach offers potential to facilitate efficient policy/decision-making and rapid response in mitigations of damages caused by natural disasters.
KW - Space–time
KW - natural hazards
KW - situational awareness
KW - social media
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U2 - 10.1080/15230406.2018.1483740
DO - 10.1080/15230406.2018.1483740
M3 - Article
AN - SCOPUS:85048779372
VL - 46
SP - 334
EP - 346
JO - Cartography and Geographic Information Science
JF - Cartography and Geographic Information Science
SN - 1523-0406
IS - 4
ER -