Smart City Gnosys

Smart city article details

Title	A New Method Of Automatic Content Analysis In Disaster Management
ID_Doc	3082
Authors	Burak Can A.; Burak Parlak I.; Acarman T.
Year	2022
Published	10th International Symposium on Digital Forensics and Security, ISDFS 2022
DOI	http://dx.doi.org/10.1109/ISDFS55398.2022.9800778
Abstract	This study proposes a new approach to investigate the social media for disaster management. Twitter usage during an earthquake becomes a multimodal backbone in order to share the knowledge through the different aspects of the disaster. Planning the emergencies is the bottleneck of the rescue organizations in time-limited rescue intervention. Exploring the general population in the epicenter of earthquake would provide vital knowledge in rescue planning. Social media is considered as a common critical source of human information during the power outage. In this study, we focused on the analysis of rescue and non rescue topics for the 2020 Izmir earthquake. Our method analysis revealed the most important disaster topics that can be derived so that rescue organizations can successfully utilize such data. Our results provide insights into the spatio-temporal distribution of earthquake rescue/non rescue terms to identify Twitter-based discussions related to the 2020 Izmir earthquake. © 2022 IEEE.
Author Keywords	deep learning; natural language processing; smart city; text processing; topic modelling

Id	Similarity	Authors	Title	Published
33375	0.862	Ma Z.; Li L.; Hemphill L.; Baecher G.B.; Yuan Y.	Investigating Disaster Response For Resilient Communities Through Social Media Data And The Susceptible-Infected-Recovered (Sir) Model: A Case Study Of 2020 Western U.S. Wildfire Season	Sustainable Cities and Society, 106 (2024)
52030	0.862	Khatoon S.; Asif A.; Hasan M.M.; Alshamari M.	Social Media-Based Intelligence For Disaster Response And Management In Smart Cities	Springer Optimization and Its Applications, 186 (2022)