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1. Disaster privacy/privacy disaster

   https://doi.org/10.1002/asi.24353  

   Sanfilippo, Madelyn R.; Shvartzshnaider, Yan; Reyes, Irwin; Nissenbaum, Helen; Egelman, Serge (March 2020, Journal of the Association for Information Science and Technology)
2. Patterns of government disaster policy response in Peru

   https://doi.org/10.1016/j.worlddev.2024.106707  

   McLaughlin_Mitchell, Sara; Pizzi, Elise (October 2024, World Development)

   Our study introduces a new quantitative dataset of government disaster responses for 183 disasters in Peru from 1900 to 2020. We examine disaster responses in the form of relocation of affected individuals, restrictions on movement, reconstruction of damaged areas, and regulations of third-party disaster relief. Prior analyses of large earthquakes and El Niño events in Peru reveal that government response to hazards shapes the outcomes for social, conflict, and economic outcomes. Our dataset contributes quantitative coding of a much larger sample of disasters to identify useful patterns in disaster response. We show that the Peruvian government is the most active actor in disaster response, although international organizations and non-governmental organizations are active in nearly a third of all disasters. Restrictions and relocation of affected populations occur, but this tends to be temporary, rather than long-term solutions to mitigate risks from future disasters. Relocation of affected people occurs more often for floods and landslides, while regulation of third-party activities occurs more frequently with floods and extreme temperature events; other disaster response policies do not vary across disaster types. Disaster responses have also shifted over time, with the government providing more funds for post-disaster reconstruction and coordinating with outside aid groups more actively in recent decades. The results demonstrate the feasibility and importance of tracking patterns of response across hazard events to fully understand the role of government in disaster response. Our larger data collection project will provide similar data for all countries over time, which will help us situate Peru’s patterns of disaster response in the larger disaster management landscape and understand how government policy choices influence political violence, migration, and other political dynamics. 

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3. Disaster reconnaissance framework for sustainable post-disaster materials management

   https://doi.org/10.1016/j.wasman.2023.07.010  

   Yeşiller, Nazli; Hanson, James L.; Wartman, Joseph; Turner, Benjamin; Gardiner, Andrea; Manheim, Derek C.; Choi, Juyeong (September 2023, Waste Management)

   A first foundational assessment is provided for disaster debris reconnaissance that includes identifying tools and techniques for reconnaissance activities, identifying challenges in field reconnaissance, and identifying and developing preliminary guidelines and standards based on advancements from a workshop held in 2022. In this workshop, reconnaissance activities were analyzed in twofold: in relation to post-disaster debris and waste materials and in relation to waste management infrastructure. A four-phase timeline was included to capture the full lifecycle of management activities ranging from collection to temporary storage to final management route: pre-disaster or pre-reconnaissance, post-disaster response (days/weeks), short-term recovery (weeks/months), and long-term recovery (months/years). For successful reconnaissance, objectives of field activities and data collection needs; data types and metrics; and measurement and determination methods need to be identified. A reconnaissance framework, represented using a 3x2x2x4 matrix, is proposed to incorporate data attributes (tools, challenges, guides), reconnaissance attributes (debris, infrastructure; factors, actions), and time attributes (pre-event, response, short-term, long-term). This framework supports field reconnaissance missions and protocols that are longitudinally based and focused on post-disaster waste material and infrastructure metrics that advance sustainable materials management practices. To properly frame and develop effective reconnaissance activities, actions for all data attributes (tools, challenges, guides) are proposed to integrate sustainability and resilience considerations. While existing metrics, tools, methods, standards, and protocols can be adapted for sustainable post-disaster materials management reconnaissance, development of new approaches are needed for addressing unique aspects of disaster debris management. 

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4. Sympathy Detection in Disaster Twitter Data

   Li, Yingjie; Park, Seoyeon; Caragea, Cornelia; Caragea, Doina; Tapia, Andrea (April 2019, Proceedings of the 16th International Conference on Information Systems for Crisis Response And Management)

   Franco, Z.; González, J.J.; Canós, J.H. (Ed.)
5. Sarcasm Detection in a Disaster Context

   Sosea, Tiberiu; Li, Junyi Jessy; Caragea, Cornelia (May 2024, Proceedings of the 2024 Joint International Conference on Computational Linguistics, Language Resources and Evaluation (LREC-COLING 2024))

   During natural disasters, people often use social media platforms such as Twitter to ask for help, to provide information about the disaster situation, or to express contempt about the unfolding event or public policies and guidelines. This contempt is in some cases expressed as sarcasm or irony. Understanding this form of speech in a disaster-centric context is essential to improving natural language understanding of disaster-related tweets. In this paper, we introduce HurricaneSARC, a dataset of 15,000 tweets annotated for intended sarcasm, and provide a comprehensive investigation of sarcasm detection using pre-trained language models. Our best model is able to obtain as much as 0.70 F1 on our dataset. We also demonstrate that the performance on HurricaneSARC can be improved by leveraging intermediate task transfer learning 

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