Abstract
During the last decade, Twitter has become a robust platform for distributing messages (tweets) among numerous subscribers worldwide. Tweets tend to increase significantly during and around the occurrence of natural hazards. While Twitter is used for near real-time alerts, processes for extracting reported damage from tweets and resolving their geographical spread in high resolution are under development. In this study, we attempt to examine what was the spatiotemporal distribution of the tweets associated with the November 2016 fire in Haifa (Israel). The acquired tweets were classified and filtered using topic modeling and RCNN (Recurrent Convolutional Neural Network), a portion of them was georeferenced, and their hyperlocal spatiotemporal patterns were examined. It was found that the tweets' sentiment corresponds to the fire's cascading events, while their spatial and temporal distribution is equivalent to most of the actual reports. Despite large uncertainties in the process of examining tweets, the results indicated that Twitter could serve as another layer of near real-time information to assist decision-makers and emergency agencies during and after cascading catastrophes striking a small-scale city.
Original language | English |
---|---|
Article number | 103720 |
Journal | International Journal of Disaster Risk Reduction |
Volume | 92 |
DOIs | |
State | Published - 15 Jun 2023 |
Bibliographical note
Funding Information:This research was supported by the Israel National Knowledge and Research Center for Emergency Readiness, which is funded by the Ministry of Science and Technology of Israel and the National Emergency Management Authority at the Ministry of Defense of Israel (Grant #3-14737 ).
Funding Information:
We wish to acknowledge Alexander Logovinsky and Julia Blues from the University of Haifa, for assisting in the data acquisition process; Tomer Toledo and Menachem Brief from the Technion, Israel Institute of Technology, for their help in data operations; Guy Shachar for assisting with fire data; and Michal Ben Gal, Deborah Shmueli, and Rotem Barkan, for their kind aid in bringing this paper to publication. This research was supported by the Israel National Knowledge and Research Center for Emergency Readiness, which is funded by the Ministry of Science and Technology of Israel and the National Emergency Management Authority at the Ministry of Defense of Israel (Grant #3-14737).
Publisher Copyright:
© 2023 Elsevier Ltd
Keywords
- Haifa
- Natural hazards
- Spatiotemporal analysis
- Wildfire
ASJC Scopus subject areas
- Geotechnical Engineering and Engineering Geology
- Safety Research
- Geology