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Louise K. Comfort, Brian A. Chalfant, Jee Eun Song, Mengyao Chen, & Brian Colella. (2014). Managing information processes in disaster events: The impact of superstorm sandy on business organizations. 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. 230–239). University Park, PA: The Pennsylvania State University.
Abstract: Building community resilience to natural disasters represents a major policy priority for the United States as hazards impact vulnerable urban regions with increasing frequency and severity. Applying network analysis techniques, we examine the dynamics of emergency response to Superstorm Sandy, which struck the United States east coast in late October 2012 and caused over $72 billion in damages. Drawing on a variety of data sources and analytical techniques, we document the storm's impact on a system of interacting private, public, and nonprofit organizations. We find that the storm's response network exhibited clear patterns of information gaps and flows among different types of organizations. Our findings suggest a general lack of communication between government agencies and businesses, an area of potential improvement in future regional-scale emergency response systems.
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Glenn I. Hawe, Duncan T. Wilson, Graham Coates, & Roger S. Crouch. (2012). STORMI: An agent-based simulation environment for evaluating responses to major incidents in the UK. In Z.Franco J. R. L. Rothkrantz (Ed.), ISCRAM 2012 Conference Proceedings – 9th International Conference on Information Systems for Crisis Response and Management. Vancouver, BC: Simon Fraser University.
Abstract: This paper describes work-in-progress regarding STORMI, an agent-based simulation environment for evaluating the response by the emergency services to hypothetical major incidents in the UK. At present, STORMI consists of two main components: a Scenario Designer and a Simulator. The Scenario Designer enables the setting up of a hypothetical multi-site mass casualty incident anywhere in the UK, along with the resources which may be considered for responding to it. This provides input to the Simulator, which through its Multiple Program Multiple Data architecture, models the agents and their environment at a higher level of detail inside incident sites than it does outside, thus focusing attention on the areas of most interest. Furthermore, the multiple programs of the Simulator execute concurrently, thus targeting multi-core processors. © 2012 ISCRAM.
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Teun Terpstra, Richard Stronkman, Arnout De Vries, & Geerte L. Paradies. (2012). Towards a realtime Twitter analysis during crises for operational crisis management. In Z.Franco J. R. L. Rothkrantz (Ed.), ISCRAM 2012 Conference Proceedings – 9th International Conference on Information Systems for Crisis Response and Management. Vancouver, BC: Simon Fraser University.
Abstract: Today's crises attract great attention on social media, from local and distant citizens as well as from news media. This study investigates the possibilities of real-time and automated analysis of Twitter messages during crises. The analysis was performed through application of an information extraction tool to nearly 97,000 tweets that were published shortly before, during and after a storm hit the Pukkelpop 2011 festival in Belgium. As soon as the storm hit the festival tweet activity increased exponentially, peaking at 576 tweets per minute. The extraction tool enabled analyzing tweets through predefined (geo)graphical displays, message content filters (damage, casualties) and tweet type filters (e.g., retweets). Important topics that emerged were 'early warning tweets', 'rumors' and the 'self-organization of disaster relief' on Twitter. Results indicate that automated filtering of information provides valuable information for operational response and crisis communication. Steps for further research are discussed. © 2012 ISCRAM.
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