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Sung Pil Moon, Yikun Liu, Steven O. Entezari, Afarin Pirzadeh, Andrew Pappas, & Mark Pfaff. (2013). Top health trends: An information visualization tool for awareness of local health trends. 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. 177–187). KIT; Baden-Baden: Karlsruher Institut fur Technologie.
Abstract: We developed an intelligent information visualization tool to enable public health officials to detect healthrelated trends in any geographic area of interest, based on Twitter data. Monitoring emergent events such as natural disasters, disease outbreaks, and terrorism is vital for protecting public health. Our goal is to support situation awareness (SA) for personnel responsible for early detection and response to public health threats. To achieve this goal, our application identifies the most frequently tweeted illnesses in a ranked chart and map for a selected geographic area. Automated processes mine and filter health-related tweets, visualize changes in rankings over time, and present other keywords frequently associated with each illness. User-centered visualization techniques of monitoring, inspecting, exploring, comparing and forecasting supports all the three stages of SA. An evaluation conducted with experts in health-related domains provided significant insights about awareness of localized health trends and their practical use in their daily work.
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Ahmed Nagy, & Jeannie Stamberger. (2012). Crowd sentiment detection during disasters and crises. 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: Microblogs are an opportunity for scavenging critical information such as sentiments. This information can be used to detect rapidly the sentiment of the crowd towards crises or disasters. It can be used as an effective tool to inform humanitarian efforts, and improve the ways in which informative messages are crafted for the crowd regarding an event. Unique characteristics of microblogs (lack of context, use of jargon etc) in Tweets expressed by a message-sharing social network during a disaster response require special handling to identify sentiment. We present a systematic evaluation of approaches to accurately and precisely identify sentiment in these Tweets. This paper describes sentiment detection expressed in 3698 Tweets, collected during the September 2010, San Bruno, California gas explosion and resulting fires. The data collected was manually coded to benchmark our techniques. We start by using a library of words with annotated sentiment, SentiWordNet 3.0, to detect the basic sentiment of each Tweet. We complemented that technique by adding a comprehensive list of emoticons, a sentiment based dictionary and a list of out-of-vocabulary words that are popular in brief, online text communications such as lol, wow, etc. Our technique performed 27% better than Bayesian Networks alone, and the combination of Bayesian networks with annotated lists provided marginal improvements in sentiment detection than various combinations of lists. © 2012 ISCRAM.
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Babajide Osatuyi, & Michael J. Chumer. (2010). An empirical investigation of alert notifications: A temporal analysis approach. 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: As the deployment of situational awareness mechanisms such as geothermal sensors, use of social network sites, and information and communication technologies (e.g., cell phones) become increasingly widespread to emergency responders, the problem of alert analysis has become very important. Broadcast of large amounts of alerts sent back to command centers for processing may impair the ability of analysts to connect dots that may otherwise adequately enable them to make informed decisions in a timely fashion. This paper investigates trends and patterns embedded in alert notifications generated over a given period of time in order to uncover correlations that may exist in the data. Data for this study are obtained from the National Center for Crisis and Continuity Coordination (NC4). We employ classical time series analysis to understand, explain and predict trends and patterns in the data. This work presents results obtained thus far in the quest for the effect of passage of time on alert patterns. Implications of this work in practice and research are discussed.
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Christian Reuter, Oliver Heger, & Volkmar Pipek. (2013). Combining real and virtual volunteers through social media. 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. 780–790). KIT; Baden-Baden: Karlsruher Institut fur Technologie.
Abstract: Recent studies have called attention to the improvement of “collaborative resilience” by fostering the collaboration potentials of public and private stakeholders during disasters. With our research we consider real and virtual volunteers in order to detect conditions for cooperation among those citizen groups through social media. Therefore we analysed the usage of Twitter during a tornado crisis to look for role patterns and aspects that helped volunteer groups in the virtual to emerge, and matched the data with an interview study on experiences, attitudes, concerns and potentials professional emergency services recounted in the emergence of volunteer groups in the real. While virtual groups seem to easily form and collaborate, the engagement of real volunteers is decreasing according to the perception of professionals. We discuss the dynamics in both tendencies and suggest design implications (use of existing social networks, promotion and awareness, connection among volunteers, connection to emergency services and systems) to support both types of volunteer groups, which lead to a software prototype.
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Caroline Rizza, & Ângela Guimarães Pereira. (2014). Building a resilient community through social network: Ethical considerations about the 2011 Genoa 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. 289–293). University Park, PA: The Pennsylvania State University.
Abstract: This paper considers the role of social media in the response to the flooding of 2011 in Genoa (Italy), caused by flash floods during torrential rainfall. Volunteer students created a Facebook page to communicate with citizens and organize support and rescue activities. In this paper, we first look at the story of the 2011 Genoa floods from the point of view of the news media to gain insights into the imaginaries behind the use of social media in situations of natural disaster. Second, we look at a communication partnership between citizenry and public authorities for its value in building resilience to disaster among communities. Ethical and social dimensions of these partnerships are analysed.
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Axel Schulz, Tung Dang Thanh, Heiko Paulheim, & Immanuel Schweizer. (2013). A fine-grained sentiment analysis approach for detecting crisis related microposts. 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. 846–851). KIT; Baden-Baden: Karlsruher Institut fur Technologie.
Abstract: Real-time information from microposts like Twitter is useful for applications in the crisis management domain. Currently, that potentially valuable information remains mostly unused by the command staff, mainly because the sheer amount of information cannot be handled efficiently. Sentiment analysis has been shown as an effective tool to detect microposts (such as tweets) that contribute to situational awareness. However, current approaches only focus on two or three emotion classes. But using only tweets with negative emotions for crisis management is not always sufficient. The amount of remaining information is still not manageable or most of the tweets are irrelevant. Thus, a more fine-grained differentiation is needed to identify relevant microposts. In this paper, we show the systematic evaluation of an approach for sentiment analysis on microposts that allows detecting seven emotion classes. A preliminary evaluation of our approach in a crisis related scenario demonstrates the applicability and usefulness.
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Lise Ann St. Denis, Leysia Palen, & Kenneth M. Anderson. (2014). Mastering social media: An analysis of Jefferson County's communications during 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. 737–746). University Park, PA: The Pennsylvania State University.
Abstract: We report on the social media communications and work practices of the Jefferson County Type III Incident Management Team during the September 2013 Colorado Floods. In this case study, we examine flood-related communications across three platforms: Facebook, Twitter, and the team's blog for insight into how this innovative team coordinated their communications to meet the information needs of a community outside of the media spotlight. Using a mixed method approach of interviews and social media content analysis, we describe their online behaviors in relation to the needs of the emergency response as a whole. We report on adaptations to their work practice that allowed them to extend traditional communications with social media to create an integrated communication plan. Finally, we look to the team's experiences for direction in how to use social media in emergencies generally.
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Kate Starbird, & Jeannie Stamberger. (2010). Tweak the tweet: Leveraging microblogging proliferation with a prescriptive syntax to support citizen reporting. 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: In this paper, we propose a low-tech solution for use by microbloggers that could enhance their ability to rapidly produce parsable, crisis-relevant information in mass emergencies. We build upon existing research on the use of social media during mass emergencies and disasters. Our proposed intervention aims to leverage the affordances of mobile microblogging and the drive to support citizen reporting within current behavioral Twitter-based microblogging practice. We introduce a prescriptive, tweet-based syntax that could increase the utility of information generated during emergencies by gently reshaping current behavioral practice. This offering is grounded in an understanding of current trends in norm evolution of Twitter use, an evolution that has progressed quickly but appears to be stabilizing around specific textual conventions.
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Kate Starbird, Grace Muzny, & Leysia Palen. (2012). Learning from the crowd: Collaborative filtering techniques for identifying on-the-ground Twitterers during mass disruptions. 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: Social media tools, including the microblogging platform Twitter, have been appropriated during mass disruption events by those affected as well as the digitally-convergent crowd. Though tweets sent by those local to an event could be a resource both for responders and those affected, most Twitter activity during mass disruption events is generated by the remote crowd. Tweets from the remote crowd can be seen as noise that must be filtered, but another perspective considers crowd activity as a filtering and recommendation mechanism. This paper tests the hypothesis that crowd behavior can serve as a collaborative filter for identifying people tweeting from the ground during a mass disruption event. We test two models for classifying on-the-ground Twitterers, finding that machine learning techniques using a Support Vector Machine with asymmetric soft margins can be effective in identifying those likely to be on the ground during a mass disruption event. © 2012 ISCRAM.
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Keri K. Stephens, Jessica L. Ford, Ashley Barrett, & Michael J. Mahometa. (2014). Alert networks of ICTs and sources in campus emergencies. 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. 652–661). University Park, PA: The Pennsylvania State University.
Abstract: This study contributes an understanding of how ICTs and varying information sources work together during emergency alerts. It builds on the prior work on campus active shooter events by examining an organization that used a range of ICTs including mobile devices, social media, organizational tools, and news media, to notify their stakeholders about an emergency. The study design used a survey to capture the responses from a random sample of over 1000 stakeholders-students, faculty, and staff-who were notified of an active shooter emergency. The findings from the first three notifications suggest that messages reaching the most stakeholders were (a) sent by official sources through ICTs like mobile phones; (b) official email communication, and (c) messages that included face-to-face communication. While 11 different ICTs were included in the study, mass media (i.e., television and radio), and social media (Twitter and Facebook) did not function substantially in the emergency alert process.
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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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Evan A. Sultanik, & Clayton Fink. (2012). Rapid geotagging and disambiguation of social media text via an indexed gazetteer. 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: Microblogging services like Twitter afford opportunities for real time determination of situation awareness during crises as people report, via their statuses, information about events on the ground. An important component of the information included in a tweet are mentions of place names that may be sites of damage, injuries, or relief efforts. Methods for extracting these place names and determining the actual location being referenced are an essential part of the suite of tools required for automated extraction of situation awareness from tweets. Extracting and disambiguating place name mentions from text have been areas of extensive research. Twitter, however, presents challenges given the 140 character restriction on status and the informal, abbreviated language that are a norm in this communication channel. Named entity recognizers, which are dependent on labeled training data, may not be useful in this medium for extracting location mentions because the typical training domains for these taggers are absent the noise found in Twitter statuses. Additionally, the contextual information that is necessary for disambiguating place names is not always present. In this paper, we demonstrate a new technique, RapidGeo, for extracting and disambiguating place names from a location specific Twitter feed using an unsupervised technique for tagging location mentions and relying on the known geographic context of the feed for disambiguation. Our location tagging technique performs much better than an off-the-shelf named entity recognizer and we achieve reasonable precision in disambiguating extracted place names. We argue that such fast, high precision, unsupervised approaches are needed when important, actionable information is required from noisy data sources such as Twitter. © 2012 ISCRAM.
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Jeannette N. Sutton. (2010). Twittering Tennessee: Distributed networks and collaboration following a technological disaster. 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: Informal communication channels are often the primary means by which time-sensitive hazard information first reaches members of the public. The capacity for informal communications has been recently transformed by the widespread adoption of social media technologies, such as the micro-blogging service Twitter, which allows individuals to interact with a broad audience over great distances. During a disaster or crisis event, this networked communication mechanism provides a means to communicate information and facilitate collaboration both locally and among distributed networks. This paper examines the use of Twitter following a technological disaster, showing how geographically dispersed individuals broadcast information about the impact of the disaster and its long-term effects, in contrast with the dearth of participation among public officials and industry representatives. Non-local users challenged authoritative accounts of the disaster and corrected misinformation. Conclusions are provided for policy makers and suggestions are offered for further research.
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Jeannette N. Sutton, Emma S. Spiro, Britta Johnson, Sean M. Fitzhugh, Mathew Greczek, & Carter T. Butts. (2012). Connected communications: Network structures of official communications in a technological disaster. 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: Informal online communication channels are being utilized for official communications in disaster contexts. Channels such as networked microblogging enable public officials to broadcast messages as well as engage in direct communication exchange with individuals. Here we investigate online information exchange behaviors of a set of state and federal organizations during the Deepwater Horizon 2010 oil spill disaster. Using data from the popular microblogging service Twitter, we analyze the roles individual organizations play in the dissemination of information to the general public online, and the conversational microstructure of official posts. We discuss characteristics and features of following networks, centrality, and conversational dynamics that may affect information exchange in disaster. This research provides insight into the use of networked communications during an event of heightened public concern, describes implications of conversational features, and suggests directions for future research. © 2012 ISCRAM.
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Andrea H. Tapia, Nicolas LaLone, & Hyun-Woo Kim. (2014). Run amok: Group crowd participation in identifying the bomb and bomber from the Boston marathon bombing. 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. 265–274). University Park, PA: The Pennsylvania State University.
Abstract: In this paper we tell a version of the story of the bombing of the Boston Marathon. At first, two online groups gathered images, video and textual information concerning the bombing of the Boston Marathon and shared these with the FBI and amongst themselves. Secondly, these groups then created mechanisms to conduct their own investigation into the identities of the perpetrators. Finally, the larger national media followed the results of these online group investigations and reported these as fact to a national audience. We choose Twitter as our data repository and conducted quantitative analyses of tweets sent during the Boston Bombing. The implications for not incorporating public crowd participation within the standard operating procedures of emergency services may result in either a loss of public confidence in the slow-moving nature of official response to uncontrollable, dangerous and irresponsible public and media participation that exacerbates the negative effects of any disaster.
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Massimiliano Tarquini, & Maurizio Morgano. (2013). Ethical challenges of participatory sensing for crisis information management. 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. 421–425). KIT; Baden-Baden: Karlsruher Institut fur Technologie.
Abstract: “Participatory Sensing is an approach to data collection and interpretation in which individuals, acting alone or in groups, use their personal mobile devices and web services to systematically explore interesting aspects of their worlds ranging from health to culture.”[ http://www.mobilizingcs.org/about/participatory-sensing] Data from the physical world of sensors and the virtual world of social networks and Linked Data can be combined into interesting high-level information. Sensor data can assist in localized information retrieval by giving the search engine direct access to events happening locally in the real world. Participatory sensing enables individuals and communities to collect and share granular, accurate data about a particular area. This paper describes work in progress within the FP7 EU-funded project SMART project to develop a multimedia search engine over content and information streaming from both the physical world and the Internet. We will identify some ethical problems regarding the use and storage of such data.
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Louis-Marie Ngamassi Tchouakeu, Carleen Maitland, Andrea H. Tapia, Kang Zhao, & Kartikeya Bajpai. (2010). Assessing humanitarian inter-organizational network effectiveness: The case of GlobalSympoNet. 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: This paper reports on research in progress. The objective of the study is to assess the effectiveness of multidimensional humanitarian inter-organizational networks. Especially, it investigates how organizational characteristics and network structure properties impact network effectiveness. To this end, the research develops a model of network effectiveness in the humanitarian field, using the case of GlobalSympoNet, a network of organizations/agencies engaged in humanitarian information management and exchange. Data for the research come from a series of three surveys and semi-structured interviews conducted among organizations/agencies members of GlobalSympoNet. Social network analyses are done using UCINET (Borgatti et al., 1999). Some preliminary results are presented here.
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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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Robert Thomson, Naoya Ito, Hinako Suda, Fangyu Lin, Yafei Liu., Ryo Hayasaka, et al. (2012). Trusting tweets: The Fukushima disaster and information source credibility on Twitter. 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 focuses on the micro-blogging service Twitter, looking at source credibility for information shared in relation to the Fukushima Daiichi nuclear power plant disaster in Japan. We look at the sources, credibility, and between-language differences in information shared in the month following the disaster. Messages were categorized by user, location, language, type, and credibility of information source. Tweets with reference to third-party information made up the bulk of messages sent, and it was also found that a majority of those sources were highly credible, including established institutions, traditional media outlets, and highly credible individuals. In general, profile anonymity proved to be correlated with a higher propensity to share information from low credibility sources. However, Japanese-language tweeters, while more likely to have anonymous profiles, referenced low-credibility sources less often than non-Japanese tweeters, suggesting proximity to the disaster mediating the degree of credibility of shared content. © 2012 ISCRAM.
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Sara Vieweg, Leysia Palen, Sophia B. Liu, Amanda L. Hughes, & Jeannette N. Sutton. (2008). Collective intelligence in disaster: Examination of the phenomenon in the aftermath of the 2007 Virginia Tech Shooting. In B. V. de W. F. Fiedrich (Ed.), Proceedings of ISCRAM 2008 – 5th International Conference on Information Systems for Crisis Response and Management (pp. 44–54). Washington, DC: Information Systems for Crisis Response and Management, ISCRAM.
Abstract: We report on the results of an investigation about the “informal, ” public-side communications that occurred in the aftermath of the April 16, 2007 Virginia Tech (VT) Shooting. Our on-going research reveals several examples of on-line social interaction organized around the goal of collective problem-solving. In this paper, we focus on specific instances of this distributed problem-solving activity, and explain, using an ethnomethodological lens, how a loosely connected group of people can work together on a grave topic to provide accurate results.
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Connie White, Linda Plotnick, Jane Kushma, Starr Roxanne Hiltz, & Murray Turoff. (2009). An online social network for emergency management. In S. J. J. Landgren (Ed.), ISCRAM 2009 – 6th International Conference on Information Systems for Crisis Response and Management: Boundary Spanning Initiatives and New Perspectives. Gothenburg: Information Systems for Crisis Response and Management, ISCRAM.
Abstract: Online Social Networking Sites (SNS) are becoming extremely popular and can be employed in a variety of contexts. They permit the establishment of global relationships that are domain related or can be based on some general need shared by the participants. Emergency domain related websites, each with their own stated mission, are becoming widespread. Can a social network offer a solution to bringing emergency domain-related entities together as a 'one stop shop?' We propose to investigate whether the social network paradigm can be used to enable individuals and organizations to collaborate in mutually beneficial ways, in all stages of emergency management: mitigation, preparedness, response and recovery. Emergency management students were surveyed to examine the concept of social networks and their acceptance as a potential tool. The results of this exploratory research show overwhelming agreement that SNS should be considered a viable solution to the problems plaguing information dissemination and communications in the emergency domain.
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Hiroko Wilensky. (2014). Twitter as a navigator for stranded commuters during the great east Japan earthquake. 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. 697–706). University Park, PA: The Pennsylvania State University.
Abstract: The increased use of social media, such as Twitter, was widely reported on Japanese media after the Great East Japan Earthquake of March 11, 2011. This study is a qualitative investigation of the use of Twitter by the stranded commuters and their supporters in the Tokyo metropolitan area immediately after the earthquake. This paper describes the possibilities and problems of Twitter use under a rapidly changing disaster situation. During the first evening of this disaster, the Japan Railroad and other railroad systems ceased their operations in the Tokyo area. This left more than five million commuters stranded in the area. Many commuters walked hours to return home, while others struggled to find temporary shelter and stayed overnight in the city. This study also explores if Twitter was an effective navigator for helping stranded commuters return home or find shelter.
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Philip Fei Wu, Yan Qu, Jennifer Preece, Kenneth R. Fleischmann, Jennifer Golbeck, Paul T. Jaeger, et al. (2008). Community response grid (CRG) for a university campus: Design requirements and implications. In B. V. de W. F. Fiedrich (Ed.), Proceedings of ISCRAM 2008 – 5th International Conference on Information Systems for Crisis Response and Management (pp. 34–43). Washington, DC: Information Systems for Crisis Response and Management, ISCRAM.
Abstract: This paper describes the initial stages of the participatory design of a community-oriented emergency response system for a university campus. After reviewing related work and the current University emergency response system, this paper describes our participatory design process, discusses initial findings from a design requirement survey and from our interactions with different stakeholders, and proposes a Web interface design for a community response grid system. The prototyping of the system demonstrates the possibility of fostering a social-network-based community participation in emergency response, and also identifies concerns raised by potential users and by the professional responder community.
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Andrea Zielinski, & Ulrich Bügel. (2012). Multilingual analysis of twitter news in support of mass emergency events. 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: Social media are increasingly becoming a source for event-based early warning systems in the sense that they can help to detect natural disasters and support crisis management during or after disasters. In this work-in-progress paper we study the problems of analyzing multilingual twitter feeds for emergency events. The present work focuses on English as “lingua franca” and on under-resourced Mediterranean languages in endangered zones, particularly Turkey, Greece, and Romania Generally, as local civil protection authorities and the population are likely to respond in their native language. We investigated ten earthquake events and defined four language-specific classifiers that can be used to detect earthquakes by filtering out irrelevant messages that do not relate to the event. The final goal is to extend this work to more Mediterranean languages and to classify and extract relevant information from tweets, translating the main keywords into English. Preliminary results indicate that such a filter has the potential to confirm forecast parameters of tsunami affecting coastal areas where no tide gauges exist and could be integrated into seismographic sensor networks. © 2012 ISCRAM.
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