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André Dittrich, & Christian Lucas. (2013). A step towards real-time analysis of major disaster events based on tweets. 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. 868–874). KIT; Baden-Baden: Karlsruher Institut fur Technologie.
Abstract: The most popular micro blogging platform Twitter has been the topic of a variety of research papers related to disaster and crisis management. As an essential first step and basis for a real-time methodology to exploit Twitter for event detection, localization and ultimately semantic content analysis, a functional model to describe the amount of tweets during a day has been developed. It was derived from a corpus of messages in an exemplary area of investigation. To satisfy the different daily behavior on particular days, two types of days are distinguished in this paper. Moreover, keyword-adjusted data is used to point out the potential of semantic tweet analysis in following steps. The consideration of spatial event descriptions in relevant tweets could significantly improve and accelerate the perception of a disaster. The results from the conducted tests demonstrate the capability of the functional model to detect events with significant social impact in Twitter data.
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Jaziar Radianti, Terje Gjøsæter, & Weiqin Chen. (2021). Slaying the SA Demons – Humans vs. Technology – A Content Analysis. In Anouck Adrot, Rob Grace, Kathleen Moore, & Christopher W. Zobel (Eds.), ISCRAM 2021 Conference Proceedings – 18th International Conference on Information Systems for Crisis Response and Management (pp. 946–958). Blacksburg, VA (USA): Virginia Tech.
Abstract: In this paper, we examine Situation Awareness (SA) and the application of Endsley's Demons of SA in different contexts and research areas and perform content analysis to examine how they are used, and to what degree they are perceived as stemming from human error or weaknesses in technology and if any suggestions for mitigation are primarily focused on the human or the technology side. Based on our findings, we propose universal design as a tool that can counter the effects of the demons of SA by improving the usability and accessibility of SA-supporting technology and thereby removing barriers to SA, rather than challenging the users to overcome not only barriers that are a result of the complexity of the situation itself, but also additional barriers that are caused by inferior and suboptimal design of the technology in use.
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Milica Stojmenovic, Cathy Dudek, Patrick Noonan, Bruce Tsuji, Devjani Sen, & Gitte Lindgaard. (2011). Identifying user requirements for a CBRNE management system: A comparison of data analysis methods. In E. Portela L. S. M.A. Santos (Ed.), 8th International Conference on Information Systems for Crisis Response and Management: From Early-Warning Systems to Preparedness and Training, ISCRAM 2011. Lisbon: Information Systems for Crisis Response and Management, ISCRAM.
Abstract: The purpose of this paper was to identify an effective user-requirements data analysis method for informing the design of a Chemical, Biological, Radiological, Nuclear, and Explosive (CBRNE) management decision support system. Data were collected from a large simulation involving medical, police, hazmat/firefighters and subjected to three different kinds of analysis methods: Social Network Analysis, Content Analysis, and Observational Analysis. While all three methods yielded valuable information, the observational method was by far the best for the present purpose.
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