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Li Heng, & Chen Tao. (2014). Multiple attributes decision making method on social stability in nuclear accident scenario. 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. 409–413). University Park, PA: The Pennsylvania State University.
Abstract: The Chernobyl nuclear accident made Europe and even the whole world clearly aware of the threats posed by nuclear accidents. When the Fukushima nuclear accident happened in Japan, the “Rush for Salt Affair” took place in some Chinese cities. Meanwhile, large numbers of anti-nuclear parades were held in many Western countries, such as Germany and the United States. Nuclear accidents have a much more serious impact on society than does an ordinary disaster, due both to the nature and characteristics of nuclear accidents, as well as asymmetric in the general public's access to reliable information. By analyzing the mechanisms and characteristics of the impacts on social stability of a nuclear accident, this paper develops a multi-attributes decision making method based on index system of social stability factors in nuclear accident scenarios.
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Shane Halse, Jess Kropczynski, & Andrea Tapia. (2018). Using Metrics of Stability to Identify Points of Failure and Support in Online Information Distribution during a Disaster. In Kees Boersma, & Brian Tomaszeski (Eds.), ISCRAM 2018 Conference Proceedings – 15th International Conference on Information Systems for Crisis Response and Management (p. 1121). Rochester, NY (USA): Rochester Institute of Technology.
Abstract: We utilize the 2012 Hurricane Sandy dataset to investigate methods to measure network stability during a crisis. While previous research on information distribution has focused on individuals that are most connected, or most willing to share information, we examined this dataset for indicators of network stability. The value of this measure is to identify the points of failure within the network. The findings in this paper provide support for the use of social network analysis within the realm of crisis response to identify the points of failure within the network.
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