Tristan Endsley, Yu Wu, & James Reep. (2014). The source of the story: Evaluating the credibility of crisis information sources. 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. 160–164). University Park, PA: The Pennsylvania State University.
Abstract: In a highly connected world, information coming from different media sources and social relationships are more quickly disseminated than ever before. Natural disasters such as Typhoon Haiyan capture attention globally. Investigations of how people respond to the credibility of different sources have implications for policy making and information systems design. In this paper, we studied how different factors (strength of social ties and sources of crisis information) affect perception of credibility of crisis information about natural disasters. Our analysis and findings indicate that for crisis information about natural disasters, people tend to trust traditional media channels, such as printed news, and televised news. The type of social tie also influences the perceived credibility of the crisis information.
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Ulrich Meissen, & Frank Fuchs-Kittowski. (2014). Towards a reference architecture of crowdsourcing integration in early warning systems. 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. 334–338). University Park, PA: The Pennsylvania State University.
Abstract: Crowdsourcing has the potential to become a crucial information source in disaster management. In order to become effective as an integrated part of disaster management systems it is important to set the general architectural foundations for such integrations beyond prototypical experiments. This paper discusses general architectural principles of the application of crowdsourcing in Early Warning Systems (EWS). An integrated architecture is proposed to use classical sensor data and crowdsourcing in an EWS solution. Therefore, typical components of crowdsourcing applications are identified and mapped to monitoring subsystems of EWS's. Three main structural variants of applying crowdsourcing in early warning systems along the example of a prototypical extension of two existing large-scale hydro-meteorological warning systems are presented.
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Ulrich Meissen, Markus Hardt, & Agnès Voisard. (2014). Towards a general system design for community-centered crisis and emergency warning systems. 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. 155–159). University Park, PA: The Pennsylvania State University.
Abstract: Early Warning Systems (EWS) provide an effective measure for better disaster preparedness, response, and mitigation. The effectiveness of EWS depends highly on the ability to distribute alert message to the persons that will be affected. In this context mobile devices play already a vital role in the ability to reach people in time and at the endangered location. Most existing approaches focus on mass dissemination methods via SMS and Cell-Broadcasting. As these approaches are effective to inform masses about a disaster with one message for all they have their weaknesses in telling the people how to respond according to their location and provide individual guidance (e.g. by maps) within specific communities. Research in disaster management gives strong evidence that the later is often crucial for better disaster response. Accordingly, we witness an increasing demand for more community-centered warnings systems solutions. This paper introduces the general foundations and architecture for alert services on mobile devices that adapt incoming alert information to the profile and situation of user groups and even individual users. The approach is scalable for different communitycentered warning systems. Its first applicability and community engagement effects are shown in the example of the community-centered public disaster alert system in Germany and a target group specific weather hazard alert system, KATWARN and WIND with currently over 2.5 million subscribed users, which was developed by the authors.
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Vitaveska Lanfranchi, Stuart N. Wrigley, Neil Ireson, Uta Wehn, & Fabio Ciravegna. (2014). Citizens' observatories for situation awareness in flooding. 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. 145–154). University Park, PA: The Pennsylvania State University.
Abstract: Citizens' observatories are emerging as a means to establish interaction and co-participation between citizens and authorities during both emergencies and the day-to-day management of fundamental resources. In this paper we present a case study in which a model of citizens' observatories is being been translated into practice in the WeSenseIt project. The WeSenseIt citizens' observatory provides a unique way of engaging the public in the decision-making processes associated with water and flood management through a set of new digital technologies. The WeSenseIt citizens' observatory model is being implemented in three case studies based in the UK, the Netherlands and Italy. We describe the findings and our experiences following preliminary evaluations of the technologies and the model of co-participation and describe our future research plans.
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Vitaveska Lanfranchi, Suvodeep Mazumdar, & Fabio Ciravegna. (2014). Visual design recommendations for situation awareness in social media. 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. 792–801). University Park, PA: The Pennsylvania State University.
Abstract: The use of online Social Media is increasingly popular amongst emergency services to support Situational Awareness (i.e. accurate, complete and real-time information about an event). Whilst many software solutions have been developed to monitor and analyse Social Media, little attention has been paid on how to visually design for Situational Awareness for this large-scale data space. We describe an approach where levels of SA have been matched to corresponding visual design recommendations using participatory design techniques with Emergency Responders in the UK. We conclude by presenting visualisation prototypes developed to satisfy the design recommendations, and how they contribute to Emergency Responders' Situational Awareness in an example scenario. We end by highlighting research issues that emerged during the initial evaluation.
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Willem Treurniet, Rozemarijn Logtenberg, & Peter Groenewegen. (2014). Governance of occasional multi-sector networks. 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. 120–124). University Park, PA: The Pennsylvania State University.
Abstract: Large-scale safety and security incidents typically require the coordinated effort of multiple organisations. A networked organisation is generally seen as the most appropriate structure for coordination within safety and security collaborations. Such networks generally are mixed-sector networks in the sense that the strategic orientations of the contributing organisations differ. Our research focuses on how to prevent, overcome and cope with the tensions resulting from this mixed-sector nature. We studied cases of three major Dutch events and our preliminarily findings were that an active network governance approach contributes to a more decisive and more purposive organisation. The flexibility and decisiveness of the networked organisation can be enhanced if in addition informal network governance measures are applied. Moreover, a purposive information infrastructure, directed towards a limited number of clear priority issues, is a key enabler of the functioning of the network.
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Yiewi Li., Yu Guo, & Naoya Ito. (2014). An exploration of a social-cognitive framework for improving the human-centric risk communication. 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. 394–398). University Park, PA: The Pennsylvania State University.
Abstract: With the aim of improving human-centric risk communication, this research in progress paper argues for a social-cognitive perspective focusing on the interaction between laypeople and the information environment. A model is designed to predict laypeople's environmental risk perception and information seeking behavior. Using data from a national online survey (N=1,032), our research is an effort to test the predictive power of the socialcognitive model. Practical implications are also discussed in this paper.
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Yixing Shan, Lili Yang, & Roy Kalawsky. (2014). Exploring the prescriptive modeling of fire situation assessment. 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. 60–64). University Park, PA: The Pennsylvania State University.
Abstract: One of the key assumptions in Endsley's three-level Situation Awareness (SA) model is the critical role of mental models in the development and maintenance of SA. We explored a prescriptive way of modeling this essential mental process of the fire incident commanders' fire ground assessment. The modeling was drawn from the Fast and Frugal Heuristics (FFHs) program, given the strong parallels between its contentions on ecological rationality and the environment demanding of the emergency response context. This paper addresses a number of issues being encountered in the attempt of our empirical investigation.
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Yongzhong Sha, Jinsong Yan, & Guoray Cai. (2014). Detecting public sentiment over PM2.5 pollution hazards through analysis of Chinese microblog. 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. 722–726). University Park, PA: The Pennsylvania State University.
Abstract: Decision-making in crisis management can benefit from routine monitoring of the (social) media to discover the mass opinion on highly sensitive crisis events. We present an experiment that analyzes Chinese microblog data (extracted from Weibo.cn) to measure sentiment strength and its change in relation to the recent PM 2.5 air pollution events. The data were analyzed using SentiStrength algorithm together with a special sentiment words dictionary tailored and refined for Chinese language. The results of time series analysis on detected sentiment strength showed that less than one percent of the posts are strong-positive or strong negative. Weekly sentiment strength measures show symmetric changes in positive and negative strength, but overall trend moved towards more positive opinions. Special attention was given to sharp bursts of sentiment strength that coincide temporally with the occurrence of extreme social events. These findings suggest that sentiment strength analysis may generate useful alert and awareness of pending extreme social events.
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Yuanyuan Li, Wenguo Weng, Tao Chen, & Hongyong Yuan. (2014). A Chinese earthquake database for casualty modelling. 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. 493–497). University Park, PA: The Pennsylvania State University.
Abstract: In order to conduct empirical casualty modelling in China, Chinese historical earthquake events is the essential basis. However, commonly used casualty databases that focus on Chinese earthquakes and provide comprehensive information rarely exist. Regarding this situation, we derived an earthquake casualty database of Mainland China from authorized Chinese published data sources. The casualty database records 520 earthquake events with magnitude 5.0 and greater where at least one casualty is recorded in the time span from 186 BC through December 2011. Each earthquake case contains information on seismic parameters, deaths tolls, number of heavy injuries and light injuries, as well as areas and population of affected regions from intensity VI to intensity IV. Compared with PAGER-CAT, this casualty database provides 146 unique earthquake events and provides more detailed information on heavy injuries and light injures, as well as areas and exposure population of affected regions. This casualty database is an essential supplement for global casualty databases and provides a basis for earthquake casualty modelling on post-earthquake risk estimation in China.
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Zahra Ashktorab, Christopher Brown, Manojit Nandi, & Aron Culotta. (2014). Tweedr: Mining twitter to inform disaster response. 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. 354–358). University Park, PA: The Pennsylvania State University.
Abstract: In this paper, we introduce Tweedr, a Twitter-mining tool that extracts actionable information for disaster relief workers during natural disasters. The Tweedr pipeline consists of three main parts: classification, clustering and extraction. In the classification phase, we use a variety of classification methods (sLDA, SVM, and logistic regression) to identify tweets reporting damage or casualties. In the clustering phase, we use filters to merge tweets that are similar to one another; and finally, in the extraction phase, we extract tokens and phrases that report specific information about different classes of infrastructure damage, damage types, and casualties. We empirically validate our approach with tweets collected from 12 different crises in the United States since 2006.
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Zhenyu Yu, Chuanfeng Han, & Ma Ma. (2014). Emergency decision making: A dynamic approach. 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. 240–244). University Park, PA: The Pennsylvania State University.
Abstract: The dynamic nature of emergency decision making exerts difficulty to decision makers for achieving effective management. In this regard, we suggest a dynamic decision making model based on Markov decision process. Our model copes with the dynamic decision problems quantitatively and computationally, and has powerful expression ability to model the emergency decision problems. We use a wildfire scenario to demonstrate the implementation of the model, as well as the solution to the firefighting problem. The advantages of our model in emergency management domain are discussed and concluded in the last.
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Zhou Sen, & Bartel A. Van De Walle. (2014). How intellectual capital reduces stress on organizational decision-making performance: The mediating roles of task complexity and time pressure. 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. 220–224). University Park, PA: The Pennsylvania State University.
Abstract: Previous research claimed that organizational stress, due to task complexity and time pressure, leads to considerably negative effects on the decision-making performance of individuals and organizations. At the same time, intellectual capital (IC), in providing intangible internal and external organizational assets has a positive effect on organizational decision-making performance. This paper develops a structural equation model to analyze the relationships among IC, task complexity, time pressure and decision-making performance. Empirical data are collected from 374 participants, who are from universities, institutes, enterprises, government, with different occupations and expertise. We present two conclusions. First, IC consisting of internal capital, human capital and external capital leads to a reduced complexity of tasks and reduced time pressure and hence reduced organizational stress. Second, reduced organizational stress results in higher levels of performance for organizational decision-making.
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