Amro Al-Akkad, & Zimmermann, A. (2012). Survey: ICT-supported public participation in disasters. 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: In an increasingly networked society citizens at disaster sites utilize information and communication technology (ICT) to communicate needs or to share information. In order to understand better emergent possibilities and implications of applying ICT for supporting public participation in disasters, we surveyed 57 respondents regarding several key user aspects as perceived usefulness, socially related issues, or deployment. Surprisingly, our results show a clear tendency to use a disaster specific application instead of using everyday services as facebook or Twitter. However, such application poses the risk to loose its focus fading slowly away after once downloading it. Further study is needed to understand if these results are representative regarding public society. © 2012 ISCRAM.
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Andrea Kavanaugh, Steven D. Sheetz, Riham Hassan, Seungwon Yang, Hicham G. Elmongui, Edward A. Fox, et al. (2012). Between a rock and a cell phone: Communication and information technology use during the 2011 Egyptian uprising. 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: Many observers heralded the use of social media during recent political uprisings in the Middle East even dubbing Iran's post election protests a “Twitter Revolution”. We seek to put into perspective the use of social media in Egypt during the mass political demonstrations in 2011. We draw on innovation diffusion theory to argue that these media could have had an impact beyond their low adoption rates due to other factors related to demographics and social networks. We supplement our social media data analysis with survey data we collected in June 2011 from an opportunity sample of Egyptian youth. We conclude that in addition to the contextual factors noted above, the individuals within Egypt who used Twitter during the uprising have the characteristics of opinion leaders. These findings contribute to knowledge regarding the role of opinion leaders and social media, especially Twitter, during violent political demonstrations. © 2012 ISCRAM.
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Anjum, U., Zadorozhny, V., & Krishnamurthy, P. (2023). Localization of Events Using Neural Networks in Twitter Data. In Jaziar Radianti, Ioannis Dokas, Nicolas Lalone, & Deepak Khazanchi (Eds.), Proceedings of the 20th International ISCRAM Conference (pp. 909–919). Omaha, USA: University of Nebraska at Omaha.
Abstract: In this paper, we develop a model with neural networks to localize events using microblogging data. Localization is the task of finding the location of an event and can be done by discovering event signatures in microblogging data. We use the deep learning methodology of Bi-directional Long Short-Term Memory (Bi-LSTM) to learn event signatures. We propose a methodology for labeling the Twitter date for use in Bi-LSTM However, there might not be enough data available to train the Bi-LSTM and learn the event signatures. Hence, the data is augmented using generative adversarial networks (GAN). Finally, we combine event signatures at different temporal and spatial granularity to improve the accuracy of event localization. We use microblogging data collected from Twitter to evaluate our model and compare it with other baseline methods.
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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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Kartikeya Bajpai, & Anuj Jaiswal. (2011). A framework for analyzing collective action events on Twitter. 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: Recent years have witnessed multiple international protest movements which have purportedly been greatly affected by the use of Twitter, a micro-blogging platform. Social movement actors in Iran, Moldova, Kyrgyzstan and Thailand are thought to have utilized Twitter to spread information, co-ordinate protest activities, evade government censorship and, in some cases, to spread misinformation. We propose a framework for conceptualizing and analyzing Twitter data related to contentious collective action crises. Our primary research goal is to delineate a framework informed with a social movements lens and to demonstrate the framework by means of Twitter usage data related to the Thailand protests of 2010. Our proposed framework concerns itself with two aspects of protest activities and Twitter usage, namely, analyzing the content and structure of messages and our construct of Twitter protest waves.
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Justine I. Blanford, Jase Bernhardt, Alexander Savelyev, Gabrielle Wong-Parodi, Andrew M. Carleton, David W. Titley, et al. (2014). Tweeting and tornadoes. 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. 319–323). University Park, PA: The Pennsylvania State University.
Abstract: Social Media and micro-blogging is being used during crisis events to provide live up-to-date information as events evolve (before, during and after). Messages are posted by citizens or public officials. To understand the effectiveness of these messages, we examined the content of geo-located Twitter messages (“tweets”) sent during the Moore, Oklahoma tornado of May 20th, 2013 (+/-1day) to explore the spatial and temporal relationships of real-time reactions of the general public. We found a clear transition of topics during each stage of the tornado event. Twitter was useful for posting and retrieving updates, reconstructing the sequence of events as well as capturing people's reactions leading up to, during and after the tornado. A long-term goal for the research reported here is to provide insights to forecasters and emergency response personnel concerning the impact of warnings and other advisory messages.
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Lindsley G. Boiney, Bradley Goodman, Robert Gaimari, Jeffrey Zarrella, Christopher Berube, & Janet Hitzeman. (2008). Taming multiple chat room collaboration: Real-time visual cues to social networks and emerging threads. In B. V. de W. F. Fiedrich (Ed.), Proceedings of ISCRAM 2008 – 5th International Conference on Information Systems for Crisis Response and Management (pp. 660–668). Washington, DC: Information Systems for Crisis Response and Management, ISCRAM.
Abstract: Distributed teams increasingly rely on collaboration environments, typically including chat, to link diverse experts for real time information sharing and decision-making. Current chat-based technologies enable easy exchange of information, but don't focus on managing those information exchanges. Important cues that guide face-to-face collaboration are either lost or missing. In some military environments, operators may juggle over a dozen chat rooms in order to collaborate on complex missions. This often leads to confusion, overload, miscommunication and delayed decisions. Our technology supports chat management. A summary display bar reduces the number of chat rooms operators need open by providing high level situational awareness pointers, in real-time, to: a) rooms with increasing message activity levels, b) rooms in which important collaborators are participating (those in the operator's social network), and c) rooms in which operator-selected keywords are used. This ability to peripherally monitor less critical chat rooms reduces operator overload, while enhancing the ability to rapidly detect important emerging discussion threads. © 2008 The MITRE Corporation. All rights reserved.
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Ivan Boissières, & Eric Marsden. (2005). Organizational factors of robustness. In B. C. B. Van de Walle (Ed.), Proceedings of ISCRAM 2005 – 2nd International Conference on Information Systems for Crisis Response and Management (pp. 117–122). Brussels: Royal Flemish Academy of Belgium.
Abstract: In complex socio-technical systems, robustness is achieved through interaction between the technical structure of the system and the social and organizational structure of the operators who run the system. While the need for human oversight of complex systems is widely recognized, the impact of organizational factors on the effectiveness of the oversight function is not well understood. We have studied the social interactions between supervision and maintenance operators of the largest French telecom operator, using techniques from the sociology of organizations. Detailed analysis of the social network formed by these operators has allowed us to identify a number of factors that contribute positively or negatively to the robustness of the system.
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Belinda Braunstein, Troy Trimble, Rajesh Mishra, B.S. Manoj, Leslie Lenert, & Ramesh R. Rao. (2006). Challenges in using of distributed wireless mesh networks in emergency response. In M. T. B. Van de Walle (Ed.), Proceedings of ISCRAM 2006 – 3rd International Conference on Information Systems for Crisis Response and Management (pp. 30–38). Newark, NJ: Royal Flemish Academy of Belgium.
Abstract: Wireless Mesh Networks (WMNs) are formed by self-organized wireless nodes that use multi-hop wireless relaying. These networks are useable in a variety of situations ranging from fixed residential broadband networking based on rooftop wireless mesh nodes to emergency response networks for handling large scale disasters. Quick deployability, minimal configuration, broadband communication, and easiness of reconfigurability are the major characteristics that make WMNs a suitable choice for emergency applications. There exist several open research issues in using such WMNs for emergency response applications. We, in this paper, present a hybrid distributed wireless networking architecture, Extreme Networking System (ENS), and present large set of performance observations collected from a real distributed hybrid wireless mesh network used for supporting a medical emergency response application. We present the traffic behavior observed in our network when a client server medical emergency response application is employed. The performance observations on real-traffic scenarios for emergency response application underlines the need for focusing further research on topology control, reliability, service availability, and distributed management. We observed that though there are several challenges that need to be solved, a WMN is a favorable choice for emergency response networking.
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Raffaele Bruno, Marco Conti, & Andrea Passarella. (2008). Opportunistic networking overlays for ICT services in crisis management. In B. V. de W. F. Fiedrich (Ed.), Proceedings of ISCRAM 2008 – 5th International Conference on Information Systems for Crisis Response and Management (pp. 689–701). Washington, DC: Information Systems for Crisis Response and Management, ISCRAM.
Abstract: ICT infrastructures are a critical asset in today's Information society. Legacy telecommunication systems easily collapse in the face of disruptions due to security incidents or natural disasters. Hence, there is an urgent demand for new architectures and technologies ensuring a more efficient and dependable support for various security missions, such as disaster relief initiatives, first responder operations, critical infrastructure protection, etc. In this paper we advocate the opportunistic networking paradigm to build a self-organizing overlay ICT infrastructure for supporting dependable crisis management services. Our opportunistic framework to “glues together” surviving parts of the pre-existing infrastructure with networks deployed on-demand and users devices, and supports dependable distribution of coherent, updated, and non-contradictory information distribution. Finally, to show the potential advantages of our solution, we present initial results on the performance of different types of opportunistic infrastructures, by particularly highlighting the gains of context-aware systems.
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Cornelia Caragea, Anna Squicciarini, Sam Stehle, Kishore Neppalli, & Andrea H. Tapia. (2014). Mapping moods: Geo-mapped sentiment analysis during hurricane sandy. 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. 642–651). University Park, PA: The Pennsylvania State University.
Abstract: Sentiment analysis has been widely researched in the domain of online review sites with the aim of generating summarized opinions of product users about different aspects of the products. However, there has been little work focusing on identifying the polarity of sentiments expressed by users during disaster events. Identifying sentiments expressed by users in an online social networking site can help understand the dynamics of the network, e.g., the main users' concerns, panics, and the emotional impacts of interactions among members. Data produced through social networking sites is seen as ubiquitous, rapid and accessible, and it is believed to empower average citizens to become more situationally aware during disasters and coordinate to help themselves. In this work, we perform sentiment classification of user posts in Twitter during the Hurricane Sandy and visualize these sentiments on a geographical map centered around the hurricane. We show how users' sentiments change according not only to users' locations, but also based on the distance from the disaster.
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Diana Fischer, Carsten Schwemmer, & Kai Fischbach. (2018). Terror Management and Twitter: The Case of the 2016 Berlin Terrorist Attack. In Kees Boersma, & Brian Tomaszeski (Eds.), ISCRAM 2018 Conference Proceedings – 15th International Conference on Information Systems for Crisis Response and Management (pp. 459–468). Rochester, NY (USA): Rochester Institute of Technology.
Abstract: There is evidence that people increasingly use social networking sites like Twitter in the aftermath of terrorist attacks to make sense of the events at the collective level. This work-in-progress paper focuses on the content of Twitter messages related to the 2016 terrorist attack on the Berlin Christmas market. We chose topic modeling to investigate the Twitter data and the terror management theory perspective to understand why people used Twitter in the aftermath of the attack. In particular, by connecting people and providing a real-time communication channel, Twitter helps its users collectively negotiate their worldviews and re-establish self-esteem. We provide first results and discuss next steps.
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Rahele B. Dilmaghani, & Ramesh R. Rao. (2008). A wireless mesh infrastructure deployment with application for emergency scenarios. In B. V. de W. F. Fiedrich (Ed.), Proceedings of ISCRAM 2008 – 5th International Conference on Information Systems for Crisis Response and Management (pp. 484–494). Washington, DC: Information Systems for Crisis Response and Management, ISCRAM.
Abstract: When a disaster or emergency occurs, one of the most pressing needs is to establish a communication network for the first responders at the scene. Establishing and accessing a reliable communication infrastructure at a crisis site is crucial in order to have accurate and real-time exchange of information. Failure in the exchange of timely and crucial information or delay in allocating resources impedes early response efforts, potentially resulting in loss of life and additional economic impact. At a disaster site, the existing communication infrastructure may be damaged and therefore partially or totally unavailable; or, there may not have been previously existing infrastructure (as in the case of remote areas). A communication infrastructure within the context of emergency applications should be reliable, easily configurable, robust, interoperable in a heterogeneous environment with minimum interdependencies, and quickly deployable at low cost. A disaster scene is a chaotic environment which requires a systematic approach to abstract the system, study the flow of information and collaboration among different disciplines and jurisdictions to facilitate response and recovery efforts. We have deployed the wireless mesh infrastructure in several drills at the university campus and in the city as part of the California Institute for Telecommunications and Information Technology (Calit2) NSF-funded RESCUE project (Responding to Crises and Unexpected Events). To evaluate network performance and identify the source(s) of bottleneck, we have captured the network traffic. The lessons learned from test bed evaluations of the network based on real-world scenarios can be applied to future applications to enhance the network design and performance.
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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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Tom Duffy, Chris Baber, & Neville Stanton. (2013). Measuring collaborative sensemaking. 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. 561–565). KIT; Baden-Baden: Karlsruher Institut fur Technologie.
Abstract: Problems of collaborative sensemaking are evident in major incident response where sharing salient information is key to the shared understanding of the situation. In this paper we propose that differences in sensemaking performance can be captured through quantitative methods derived from consideration of network structure and information diffusion as the group collaborates to achieve consensus in a problem-solving task. We present analysis from a large international study in which groups of people collaborate to solve an intelligence analysis problem. Our initial analysis suggests that 'edge' groups are able to collaborate more efficiently and perform better than those which have a hierarchical control structure.
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Kevin Fall, Gianluca Iannaccone, Jayanthkumar Kannan, Fernando Silveira, & Nina Taft. (2010). A disruption-tolerant architecture for secure and efficient disaster response communications. 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: We consider the problem of providing situational awareness when citizens in a disaster are willing to contribute their own devices, such as laptops and smart phones, to gather data (text, images, audio or video) and to help forward data gathered by others. A situational awareness service processes all received data and creates annotated maps to visualize a disaster site (e.g., the status of the disaster, such as fires or floods, the location of people, food, or water). We discuss the challenges imposed on such an application when 1) the communications infrastructure in the disaster area can only provide intermittent connectivity, 2) anxious victims generate large amounts of redundant content congesting the network, and 3) the sharing of personal devices creates security and privacy threats. We present an architecture that addresses the requirements to support such a service.
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Zeno Franco, Syed Ahmed, Craig E. Kuziemsky, Paul A. Biedrzycki, & Anne Kissack. (2013). Using social network analysis to explore issues of latency, connectivity, interoperability & sustainability in community disaster response. 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. 896–900). KIT; Baden-Baden: Karlsruher Institut fur Technologie.
Abstract: Community-based disaster response is gaining attention in the United States because of major problems with domestic disaster recovery over the last decade. A social network analysis approach is used to illustrate how community-academic partnerships offer one way to leverage information about existing, mediated relationships with the community through trusted actors. These partnerships offer a platform that can be used to provide entré into communities that are often closed to outsiders, while also allowing greater access to community embedded physical assets and human resources, thus facilitated more culturally appropriate crisis response. Using existing, publically available information about funded community-academic partnerships in Wisconsin, USA, we show how social network analysis of these meta-organizations may provide critical information about both community vulnerabilities in disaster and assist in rapidly identifying these community resources in the aftermath of a crisis event that may provide utility for boundary spanning crisis information systems.
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Lida Khalili Gheidary. (2010). Social media and Iran's post-election crisis. 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 research-in-progress paper, the role of social media during the two months of the Iranian post-election crisis in Summer 2009 has been studied. In search of emergent social phenomena, particular emphasis is given to online participation and collaboration throughout social network sites. This study demonstrates the extent to which such media can gain prominence and challenge traditional practices as well as challenging the next level of research and development of social media during crisis situations.
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Nicklaus A. Giacobe, & Pamela J. Soule. (2014). Social media for the emergency manager in disaster planning and 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. 570–574). University Park, PA: The Pennsylvania State University.
Abstract: This practitioner paper outlines some of the benefits for the use of social media, from the perspective of a local-level or county-level emergency manager (EM). As compared to state and national level emergency management, because local level EMs have limited manpower and resources, social media can positively or negatively impact the effectiveness of communication before, during and after disaster strikes. Outlined in this paper are six key points where local EMs have specific needs that could be addressed by the effective use of social media and, in the opinion of the authors, represent the top issues that EMs face when considering how to leverage Twitter, Facebook, YouTube, Instagram and other social media platforms. The six needs addressed in this paper include: 1) Best practices for general social media use by EMs, 2) Social media use for internal command and control within the EM group, 3) Developing situation awareness by monitoring social media, especially prior to predicable events, 4) Communicating disaster preparedness messages through social media, 5)Using social media for gathering damage assessment information during, or immediately following a crisis,and 6) Leveraging social media volunteer groups. This short paper picks up where the Federal Emergency Management Agency's social media training leaves off and attempts to represent these six needs as use cases for researchers and developers to address in future publications and products.
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Haiyan Hao, & Yan Wang. (2020). Hurricane Damage Assessment with Multi-, Crowd-Sourced Image Data: A Case Study of Hurricane Irma in the City of Miami. In Amanda Hughes, Fiona McNeill, & Christopher W. Zobel (Eds.), ISCRAM 2020 Conference Proceedings – 17th International Conference on Information Systems for Crisis Response and Management (pp. 825–837). Blacksburg, VA (USA): Virginia Tech.
Abstract: The massive crowdsourced data generated on social networking platforms (e.g. Twitter and Flickr) provide free, real-time data for damage assessment (DA) even during catastrophes. Recent studies leveraging crowdsourced data for DA mainly focused on analyzing textual formats. Crowdsourced images can provide rich and objective information about damage conditions, however, are rarely researched for DA purposes. The highly-varied content and loosely-defined damage forms make it difficult to process and analyze the crowdsourced images. To address this problem, we propose a data-driven DA method based on multi-, crowd-sourced images, which includes five machine learning classifiers organized in a hierarchical structure. The method is validated with a case study investigating the damage condition of the City of Miami caused by Hurricane Irma. The outcome is then compared with a metric derived from NFIP insurance claims data. The proposed method offers a resource for rapid DA that supplements conventional DA methods.
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Rajesh M. Hegde, B.S. Manoj, Bashkar D. Rao, & Ramesh R. Rao. (2006). Emotion detection from speech signals and its applications in supporting enhanced QoS in emergency response. In M. T. B. Van de Walle (Ed.), Proceedings of ISCRAM 2006 – 3rd International Conference on Information Systems for Crisis Response and Management (pp. 82–91). Newark, NJ: Royal Flemish Academy of Belgium.
Abstract: Networking in the event of disasters requires new hybrid wireless architectures such as Wireless Mesh Networks (WMNs). Provisioning Quality of Service (QoS) in such networks which are quickly deployed during emergencies demand radical solutions. In this paper, we provide a new QoS approach for voice calls over a wireless mesh networks during emergency situations. According to our scheme, the contention and back-off parameters are modified based on the emotion content in the voice streams. This paper also looks at methods for detecting emotion from an incoming voice call using the speech signal. The issues of interest in such situations are whether the caller is in a state of extreme panic, moderate panic, or in a normal state of behavior. The communication network behavior should be modified to provide differentiated QoS for calls based on the degree of emotion. We use several features extracted from the speech signal like the range of pitch variation, energy in the critical bark band, range of the first three formant variations, and speaking rate among others to discriminate between the three emotional states. At the back end the Gaussian mixture modeling techniques is used to model the three emotional states of the speaker. Since a large number of features increase the computational complexity and time, a feature selection technique is employed based on the Bhattacharya distance, to select the set of features that give maximum discrimination between the classes. These set of features are employed to simulate an emotion recognition system. The results indicate a promising emotion detection rate for the three emotions. We also present the early results on detecting the emotion content in the speech and using this in the MAC layer differentiated QoS provisioning scheme. Our scheme provides an end-to-end delay performance improvement for panicked calls as high as 60% compared to normal calls.
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Benjamin Herfort, João Porto De Albuquerque, Svend-Jonas Schelhorn, & Alexander Zipf. (2014). Does the spatiotemporal distribution of tweets match the spatiotemporal distribution of flood phenomena? A study about the River Elbe Flood in June 2013. 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. 747–751). University Park, PA: The Pennsylvania State University.
Abstract: In this paper we present a new approach to enhance information extraction from social media that relies upon the geographical relations between twitter data and flood phenomena. We use specific geographical features like hydrological data and digital elevation models to analyze the spatiotemporal distribution of georeferenced twitter messages. This approach is applied to examine the River Elbe Flood in Germany in June 2013. Although recent research has shown that social media platforms like Twitter can be complementary information sources for achieving situation awareness, previous work is mostly concentrated on the classification and analysis of tweets without resorting to existing data related to the disaster, e.g. catchment borders or sensor data about river levels. Our results show that our approach based on geographical relations can help to manage the high volume and velocity of social media messages and thus can be valuable for both crisis response and preventive flood monitoring.
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Thomas Heverin, & Lisl Zach. (2010). Microblogging for crisis communication: Examination of twitter use in response to a 2009 violent crisis in the Seattle-Tacoma, Washington area. 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 research-in-progress paper reports on the use of microblogging as a communication and information sharing resource during a recent violent crisis. The goal of the larger research effort is to investigate the role that microblogging plays in crisis communication during violent events. The shooting of four police officers and the subsequent 48-hour search for the suspect that took place in the Seattle-Tacoma area of Washington in late November 2009 is used as a case study. A stream of over 6,000 publically available messages on Twitter, a popular microblogging site, was collected and individual messages were categorized as information, opinion, technology, emotion, and action-related. The coding and statistical analyses of the messages suggest that citizens use microblogging as one method to organize and disseminate crisis-related information. Additional research is in progress to analyze the types of information transmitted, the sources of the information, and the temporal trends of information shared.
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Amanda L. Hughes, & Leysia Palen. (2009). Twitter adoption and use in mass convergence and emergency events. 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: This paper offers a descriptive account of Twitter (a micro-blogging service) across four high profile, mass convergence events-two emergency and two national security. We statistically examine how Twitter is being used surrounding these events, and compare and contrast how that behavior is different from more general Twitter use. Our findings suggest that Twitter messages sent during these types of events contain more displays of information broadcasting and brokerage, and we observe that general Twitter use seems to have evolved over time to offer more of an information-sharing purpose. We also provide preliminary evidence that Twitter users who join during and in apparent relation to a mass convergence or emergency event are more likely to become long-term adopters of the technology.
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Cindy Hui, Mark Goldberg, Malik Magdon-Ismail, & William A. Wallace. (2008). Micro-simulation of diffusion of warnings. In B. V. de W. F. Fiedrich (Ed.), Proceedings of ISCRAM 2008 – 5th International Conference on Information Systems for Crisis Response and Management (pp. 424–430). Washington, DC: Information Systems for Crisis Response and Management, ISCRAM.
Abstract: This paper presents a unique view of modeling the diffusion of warnings in social networks where the network structure may change over time. Since the characteristics and actions of people in a community have significant influence on the flow of information through a network, we present an axiomatic framework for modeling the diffusion process through the concept of trust. This ongoing work provides a micro level view of the behavior of individuals and groups in a community. Preliminary experiments were made to explore how model parameters such as trust and the social network structure affect warning message belief and evacuation.
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