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Shideh Dashti, Leysia Palen, Mehdi P. Heris, Kenneth M. Anderson, T. Jennings Anderson, & Scott Anderson. (2014). Supporting disaster reconnaissance with social media data: A design-oriented case study of the 2013 Colorado floods. In and P.C. Shih. L. Plotnick M. S. P. S.R. Hiltz (Ed.), ISCRAM 2014 Conference Proceedings – 11th International Conference on Information Systems for Crisis Response and Management (pp. 632–641). University Park, PA: The Pennsylvania State University.
Abstract: Engineering reconnaissance following an extreme event is critical in identifying the causes of infrastructure failure and minimizing such consequences in similar future events. Typically, however, much of the data about infrastructure performance and the progression of geological phenomena are lost during the event or soon after as efforts move to the recovery phase. A better methodology for reliable and rapid collection of perishable hazards data will enhance scientific inquiry and accelerate the building of disaster-resilient cities. In this paper, we explore ways to support post-event reconnaissance through the strategic collection and reuse of social media data and other remote sources of information, in response to the September 2013 flooding in Colorado. We show how tweets, particularly with postings of visual data and references to location, may be used to directly support geotechnical experts by helping to digitally survey the affected region and to navigate optimal paths through the physical space in preparation for direct observation.
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Flávio E. A. Horita, & João Porto De Albuquerque. (2013). An approach to support decision-making in disaster management based on volunteer geographic information (VGI) and spatial decision support systems (SDSS). In J. Geldermann and T. Müller S. Fortier F. F. T. Comes (Ed.), ISCRAM 2013 Conference Proceedings – 10th International Conference on Information Systems for Crisis Response and Management (pp. 301–306). KIT; Baden-Baden: Karlsruher Institut fur Technologie.
Abstract: The damage caused by recent events in Japan in 2011 and USA in 2012 highlighted the need to adopt measures to increase the resilience of communities against extreme events and disasters. In addition to the conventional and official information that is necessary for adaptation to disasters, recently, common citizens residents in the affected areas also began contributing with voluntary qualified and updated information. In this context, this work-in-progress presents an approach that uses voluntary information – Also known by VGI (Volunteered Geographic Information) – As a data source for Spatial Decision Support Systems (SDSS) in order to assist the decision-making in disaster management. Our approach consists of a framework that integrates voluntary and conventional data, a SDSS and processes and methods for decision-making. As a result, it is expected that this approach will assist official organizations in disaster management by providing mechanisms and information.
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Jan Wendland, Christian Ehnis, Rodney J. Clarke, & Deborah Bunker. (2018). Sydney Siege, December 2014: A Visualisation of a Semantic Social Media Sentiment Analysis. In Kees Boersma, & Brian Tomaszeski (Eds.), ISCRAM 2018 Conference Proceedings – 15th International Conference on Information Systems for Crisis Response and Management (pp. 493–506). Rochester, NY (USA): Rochester Institute of Technology.
Abstract: Sentiment Analyses are widely used approaches to understand and identify emotions, feelings, and opinion on social media platforms. Most sentiment analysis systems measure the presumed emotional polarity of texts. While this is sufficient for some applications, these approaches are very limiting when it comes to understanding how social media users actually use language resources to make sense of extreme events. In this paper, a Sentiment Analysis based on the Appraisal System from the theory of communication called Systemic Functional Linguistics is applied to understand the sentiment of event-driven social media communication. A prototype was developed to analyze Twitter data using the Appraisal System. This prototype was applied to tweets collected during and after the Sydney Siege 2014, a hostage situation in a busy café in Sydney. Because the Appraisal System is a theorised functional communication method, the results of this analysis are more nuanced than is possible with traditional polarity based sentiment analysis.
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Murray Turoff, Connie White, Linda Plotnick, & Starr Roxanne Hiltz. (2008). Dynamic emergency response management for large scale decision making in extreme events. In B. V. de W. F. Fiedrich (Ed.), Proceedings of ISCRAM 2008 – 5th International Conference on Information Systems for Crisis Response and Management (pp. 462–470). Washington, DC: Information Systems for Crisis Response and Management, ISCRAM.
Abstract: Effective management of a large-scale extreme event requires a system that can quickly adapt to changing needs of the users. There is a critical need for fast decision-making within the time constraints of an ongoing emergency. Extreme events are volatile, change rapidly, and can have unpredictable outcomes. Large, not predetermined groups of experts and decision makers need a system to prepare for a response to a situation never experienced before and to collaborate to respond to the actual event. Extreme events easily require a hundred or more independent agencies and organizations to be involved which usually results in two or more times the number of individuals. To accomplish the above objectives we present a philosophical view of decision support for Emergency Preparedness and Management that has not previously been made explicit in this domain and describe a number of the current research efforts at NJIT that fit into this framework.
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Yulia Tyshchuk, & William A. Wallace. (2013). The use of social media by local government in response to an extreme event: Del norte county, CA response to the 2011 Japan tsunami. In J. Geldermann and T. Müller S. Fortier F. F. T. Comes (Ed.), ISCRAM 2013 Conference Proceedings – 10th International Conference on Information Systems for Crisis Response and Management (pp. 802–811). KIT; Baden-Baden: Karlsruher Institut fur Technologie.
Abstract: Social media has become increasingly important for emergency management. One example is its current use by governmental organizations to disseminate emergency-relevant information. During disaster events, it is imperative for people in affected areas to obtain accurate information. People using social media make a conscious decision to trust, act on, propagate or disregard emergency-relevant information. However, local government, in general, has not developed agreed upon ways to use social media in emergencies. This study documents how emergency management was able to successfully partner with local media and utilize social media to develop important relationships with the affected community via social media in emergencies. The study demonstrates a way to successfully utilize social media during disaster events in several ways: by closing a feedback loop between first responders and the public, by monitoring information flow, and by providing regular updates to the public.
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Connie White, Murray Turoff, & Starr Roxanne Hiltz. (2010). A real time online Delphi Decision System, V 2.0: Crisis management support during extreme events. In C. Zobel B. T. S. French (Ed.), ISCRAM 2010 – 7th International Conference on Information Systems for Crisis Response and Management: Defining Crisis Management 3.0, Proceedings. Seattle, WA: Information Systems for Crisis Response and Management, ISCRAM.
Abstract: The Delphi Decision Maker system has been designed to support the decision making needs of crisis managers, considering factors such as stress, time pressure, information overload, and uncertainty. It has been built as a module for the Sahana Disaster Management system, a free and open source system. The Design Science research paradigm was used in an iterative development process. Triangulation was employed in the evaluation, analyzing the system against the research questions using both qualitative and quantitative statistics as well as proof of concept. Modifications need to be made for real world use. A second version of the system is under development. Research findings and future research are outlined in this work in progress.
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