Wang, D., & Kogan, M. (2023). Resonance+: Augmenting Collective Attention to Find Information on Public Cognition and Perception of Risk. In Jaziar Radianti, Ioannis Dokas, Nicolas Lalone, & Deepak Khazanchi (Eds.), Proceedings of the 20th International ISCRAM Conference (pp. 487–500). Omaha, USA: University of Nebraska at Omaha.
Abstract: Microblogging platforms have been increasingly used by the public and crisis managers in crisis. The increasing volume of data has made such platforms more difficult for officials to find on-the-ground information and understand the public’s perception of the evolving risks. The crisis informatics literature has proposed various technological solutions to find relevant information from social media. However, the cognitive processes of the affected population and their subsequent responses, such as perceptions, emotional and behavioral responses, are still under-examined at scale. Yet, such information is important for gauging public perception of risks, an important task for PIOs and emergency managers. In this work, we leverage the noise-cutting power of collective attention and take cues from the Protective Action Decision Model, to propose a method that estimates shifts in collective attention with a special focus on the cognitive processes of those affected and their subsequent responses.
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Hayley Watson, & Rachel L. Finn. (2013). Privacy and ethical implications of the use of social media during a volcanic eruption: Some initial thoughts. 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. 416–420). KIT; Baden-Baden: Karlsruher Institut fur Technologie.
Abstract: In a relatively new area of research for crisis management, this working paper presents a preliminary discussion of some of the privacy and ethical implications surrounding the use of social media in the event of a crisis. The paper uses the chaos caused by the eruptions of the Eyjafjallajokull volcano in 2010 to contextualise the analysis. It begins by presenting two case studies of the use of social media by members of the public and the aviation industry during the crisis caused by the ash plume. The paper then proceeds to briefly highlight some select ethical and privacy implications stemming from the use of social media such as privacy infringements and inequality. The paper concludes by briefly summarising the findings of the paper and considering next steps for future research in this area.
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Hayley Watson, & Rachel L. Finn. (2014). Social media and the 2013 UK heat wave: Opportunities and challenges for future events. 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. 757–761). University Park, PA: The Pennsylvania State University.
Abstract: Studies examining the role of social media (SM) use in a crisis often examine the use of SM following a largescale crisis requiring an immediate response. In contrast, this working paper examines the usefulness of SM during an extended crisis, in the form of a heat wave. Authors use the 2013 UK heat wave as a case study to examine how SM was used by different stakeholders during the event, what function(s) SM had, how it was engaged with by the online community and accordingly, what value it contributed to crisis management activities. Findings show that ultimately the nature of the crisis, particularly in relation to populations who are most likely to be vulnerable to its effects, plays an integral role to the value of SM in preparation and response activities.
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Hayley Watson, Lemi Baruh, Rachel L. Finn, & Salvatore Scifo. (2014). Citizen (in)security?: Social media, citizen journalism and crisis 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. 294–298). University Park, PA: The Pennsylvania State University.
Abstract: The use of social media in a crisis has been applauded, and is witnessing an increase in uptake among those involved in crisis management activities, including citizens. Whilst some challenges have been discussed elsewhere, somewhat lacking is a discussion on the impact of sharing information on the security of those that may have been recorded. Accordingly, this working paper aims to provide preliminary results of an initial mapping task that seeks to examine the impact of the use of social media in a crisis on the social and ethical wellbeing of the security of the citizen. Authors argue that the heightened involvement of citizen journalism results in the filtering of information after its online publication which raises concerns relating to the dissemination of false information and a threat to an individual's privacy. Such issues should be adequately addressed in the encouragement and use of citizen contributions in crisis response.
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Gerhard Wickler, Stephen Potter, Austin Tate, & Jeffrey Hansberger. (2011). The virtual collaboration environment: New media for crisis response. 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: This paper concerns the use of new media technologies, including virtual worlds and web 2.0, for on-line collaborative activities, and specifically for the provision of expert advice about the response to large-scale crises. Internet technologies in general offer rich possibilities for interactions involving remote experts; however, the diversity, novelty and power of these technologies are such that to introduce them into problem-solving episodes without first developing a model of the nature of those episodes and the type of collaborative support they require, risks confusing and discouraging users. After a brief discussion of the nature of distributed collaboration and the implications this has for any technical support, we describe a virtual collaboration environment that has been developed to foster task-focused communities and support them through specific problem-solving episodes, and present some of the results of evaluation experiments.
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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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William R. Smith, Keri K. Stephens, Brett Robertson, Jing Li, & Dhiraj Murthy. (2018). Social Media in Citizen-Led Disaster Response: Rescuer Roles, Coordination Challenges, and Untapped Potential. In Kees Boersma, & Brian Tomaszeski (Eds.), ISCRAM 2018 Conference Proceedings – 15th International Conference on Information Systems for Crisis Response and Management (pp. 639–648). Rochester, NY (USA): Rochester Institute of Technology.
Abstract: Widespread disasters can overload official agencies' capacity to provide assistance, and often citizen-led groups emerge to assist with disaster response. As social media platforms have expanded, emergent rescue groups have many ways to harness network and mobile tools to coordinate actions and help fellow citizens. This study used semi-structured interviews and photo elicitation techniques to better understand how wide-scale rescues occurred during the 2017 Hurricane Harvey flooding in the Greater Houston, Texas USA area. We found that citizens used diverse apps and social media-related platforms during these rescues and that they played one of three roles: rescuer, dispatcher, or information compiler. The key social media coordination challenges these rescuers faced were incomplete feedback loops, unclear prioritization, and communication overload. This work-in-progress paper contributes to the field of crisis and disaster response research by sharing the nuances in how citizens use social media to respond to calls for help from flooding victims.
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Xiao Li, Julia Kotlarsky, & Michael D. Myers. (2023). Crowdsourcing and the COVID-19 Response in China: An Actor-Network Perspective. In V. L. Thomas J. Huggins (Ed.), Proceedings of the ISCRAM Asia Pacific Conference 2022 (pp. 240–246). Palmerston North, New Zealand: Massey Unversity.
Abstract: Crowdsourcing, serving as a distributed problem-solving and production model, can help in the response to a disaster. The current literature focuses on the flow of crowdsourced information, but the question of how crowdsourcing contributes to physical disaster workflows remains to be addressed. Based on a case study of China’s response to COVID-19, this research aims to explore the role of crowdsourcing stakeholders and how they acted to respond to the outbreak. Actor network theory is applied as the lens to elucidate the roles of different heterogeneous actors. The preliminary results indicate that socio-technical actors activated, absorbed, associated, and aligned with each other to combat the pandemic. We suggest ways to augment the actor network to address potential future outbreaks.
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Xiao LongDeng, Hui Zhang, Ya Qi Tang, & Le Yi Ren. (2015). Risk Analysis of International Spreading in 2014 Ebola Outbreak to China Compared to Social Media. In L. Palen, M. Buscher, T. Comes, & A. Hughes (Eds.), ISCRAM 2015 Conference Proceedings ? 12th International Conference on Information Systems for Crisis Response and Management. Kristiansand, Norway: University of Agder (UiA).
Abstract: The 2014 West African EbolaOutbreak raisedfrom Sierra Leone, Guinea, and Liberia at December in 2013 has been reported to cause 21296 cases and 8429 deaths until now which became the deadliest recorded in history. In this paper, we proposed the riskanalysis to assess the international spread risk from mentioned three African countries to China by GEM(Global Epidemic Mobility) Model. As another part of analysis, we crawled related online social media data of Ebola from the most four favorite online social networks (including SINA, TENCENT) in China from June to November in 2014.By analyzing these attained social media data and airline data of GEM, we found some interesting results. For example, Beijing has the most importing risk of Ebola while it has the hottest discussion on social network.. Furthermore, we showed analysis of combining social network data with geographicaldemonstration and Chinese citizen sentiment towards this disaster.
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Yajie Li, Amanda Lee Hughes, & Peter D. Howe. (2018). Communicating Crisis with Persuasion: Examining Official Twitter Messages on Heat Hazards. In Kees Boersma, & Brian Tomaszeski (Eds.), ISCRAM 2018 Conference Proceedings – 15th International Conference on Information Systems for Crisis Response and Management (pp. 469–479). Rochester, NY (USA): Rochester Institute of Technology.
Abstract: Official crisis messages need to be persuasive to promote appropriate public responses. However, little research has examined the content of crisis messages from a persuasion perspective, especially for natural hazards. This study deductively identifies five persuasive message factors (PMFs) applicable to natural hazards, including two under-examined health-related PMFs: health risk susceptibility and health impact. Using 2016 heat hazards as a case study, this paper content-analyzes heat-related Twitter messages (N=904) posted by eighteen U.S. National Weather Service Weather Forecast Offices according to the five PMFs. We find that the use of descriptions of hazard intensity is disproportionately high, with a lack of use of other PMFs. We also describe different types of statements used to signal the two health-related PMFs. We conclude with implications and recommendations relevant to practitioners and researchers in social media crisis communication.
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Yang Zhang, William Drake, Yuhong Li, Christopher Zobel, & Margaret Cowell. (2015). Fostering Community Resilience through Adaptive Learning in a Social Media Age: Municipal Twitter Use in New Jersey following Hurricane Sandy. In L. Palen, M. Buscher, T. Comes, & A. Hughes (Eds.), ISCRAM 2015 Conference Proceedings ? 12th International Conference on Information Systems for Crisis Response and Management. Kristiansand, Norway: University of Agder (UiA).
Abstract: Adaptive learning capacity is a critical component of community resilience that describes the ability of a community to effectively gauge its vulnerability to the external environment and to make appropriate changes to its coping strategies. Traditionally, the relationship between government and community learning was framed within a deterministic paradigm. Learning outcomes were understood to result from the activities of central actors (i.e., government) and flow passively into the community. The emergence of social media is fundamentally changing the ways organizations and individuals collect and share information. Despite its growing acceptance, it remains to be determined how this shift in communication will ultimately affect community adaptive learning, and therefore, community resilience. This paper presents the initial results of a mixed-methods research effort that examined the use of Twitter in local municipalities from Monmouth County, NJ after Hurricane Sandy. Using a conceptual model of organizational learning, we examine the learning outcomes following the Hurricane Sandy experience.
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Yu, X., Chen, J., & Liu, J. (2023). Examining the influence of social media on individual’s protective action taking during Covid-19 in China. In Jaziar Radianti, Ioannis Dokas, Nicolas Lalone, & Deepak Khazanchi (Eds.), Proceedings of the 20th International ISCRAM Conference (pp. 295–308). Omaha, USA: University of Nebraska at Omaha.
Abstract: In the context of COVID-19, this study utilizes the Social Mediated Crisis Communication Model (SMCC) and the Protective Action Decision Model (PADM) to investigate the relationship between social media users' protective actions and crisis information during public health crises in China. By constructing a structural equation model, this study aims to identify the influencing factors that affect social media users' personal’s cognitive, emotional, and behavioral reactions given crisis relevant information. Results findings are that warning information can significantly increase risk perception; emotional responses are not significantly affected by warning information and risk perception; risk perception has a negative impact on information gathering and sharing behavior; risk perception has a significant mediating effect on the relationship between information features and protective action.
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Yudi Chen, Angel Umana, Chaowei Yang, & Wenying Ji. (2021). Condition Sensing for Electricity Infrastructures in Disasters by Mining Public Topics from Social Media. 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. 598–608). Blacksburg, VA (USA): Virginia Tech.
Abstract: Timely and reliable sensing of infrastructure conditions is critical in disaster management for planning effective infrastructure restorations. Social media, a near real-time information source, has been widely used in the disaster domain for building timely, general situational awareness, such as urgent public needs and donations. However, the employment of social media for sensing electricity infrastructure conditions has yet been explored. This study aims to address the research gap to sense electricity infrastructure conditions through mining public topics from social media. To achieve this purpose, we proposed a systematic and customized approach wherein (1) electricity-related social media data is extracted by the classifier developed based on Bidirectional Encoder Representations from Transformers (BERT); and (2) public topics are modeled with unigrams, bigrams, and trigrams to incorporate the formulaic expressions of infrastructure conditions in social media. Electricity infrastructures in Florida impacted by Hurricane Irma are studied for illustration and demonstration. Results show that the proposed approach is capable of sensing the temporal evolutions and geographic differences of electricity infrastructure conditions.
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Yuhong Li, & Christopher Zobel. (2016). Small Businesses and Social Media Usage in the 2013 Colorado Floods. In A. Tapia, P. Antunes, V.A. Bañuls, K. Moore, & J. Porto (Eds.), ISCRAM 2016 Conference Proceedings ? 13th International Conference on Information Systems for Crisis Response and Management. Rio de Janeiro, Brasil: Federal University of Rio de Janeiro.
Abstract: The recovery of small businesses from a disaster is critical to community recovery. Such businesses can be extremely vulnerable to disasters, particularly because they often occupy a single location and have a localized customer base. Although social media is an effective platform for information dissemination, and has been extensively used in a disaster context, the way in which small businesses use social media in this context, and the effectiveness of those efforts, are still not well understood. With this in mind, this paper uses the 2013 floods along the Front Range in Colorado as a case study to help improve our understanding of how small businesses use social media in disaster situations. Characterizing the organizations' behavior involves using both qualitative and quantitative approaches, and the paper focuses on an initial qualitative analysis.
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Yuya Shibuya, & Hideyuki Tanaka. (2019). Detecting Disaster Recovery Activities via Social Media Communication Topics. In Z. Franco, J. J. González, & J. H. Canós (Eds.), Proceedings of the 16th International Conference on Information Systems for Crisis Response And Management. Valencia, Spain: Iscram.
Abstract: Enhancing situational awareness by mining social media has been widely studied, but little work has been done
focusing on recovery phases. To provide evidence to support the possibility of harnessing social media as a sensor
of recovery activities, we examine the correlations between topic frequencies on Twitter and people?s socioeconomic
recovery activities as reflected in the excess demand for used cars and housing, after the Great East
Japan Earthquake and Tsunami of 2011. Our research suggests that people in the disaster-stricken area
communicated more about recovery and disaster damages when they needed to purchase used cars, while the nonlocal
population communicated more about going to and supporting the disaster-stricken area. On the other hand,
regarding the excess demand for housing, when the local population of the disaster-stricken area started to resettle,
they communicated their opinions more than in other periods about disaster-related situations.
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Zainab Akhtar, Ferda Ofli, & Muhammad Imran. (2021). Towards Using Remote Sensing and Social Media Data for Flood Mapping. 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. 536–551). Blacksburg, VA (USA): Virginia Tech.
Abstract: Ghana's capital, the Greater Accra Metropolitan Area (GAMA) is most vulnerable to flooding due to its high population density. This paper proposes the fusion of satellite imagery, social media, and geospatial data to derive near real-time (NRT) flood maps to understand human activity during a disaster and the extent of infrastructure damage. To that end, the paper presents an automatic thresholding technique for NRT flood mapping using Sentinel-1 images where four different speckle filters are compared using the VV, VH and VV/VH polarization to determine the best polarization(s) for delineating flood extents. The VV and VH bands together on Perona-Malik filtered images achieved the highest accuracy with an F1-score of 81.6%. Moreover, all tweet text and images were found to be located in flooded regions or in very close proximity to a flooded region, thus allowing crisis responders to better understand vulnerable communities and what humanitarian action is required.
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Andrea Zielinski, Stuart E. Middleton, Laurissa N. Tokarchuk, & Xinyue Wang. (2013). Social media text mining and network analysis for decision support in natural crisis 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. 840–845). KIT; Baden-Baden: Karlsruher Institut fur Technologie.
Abstract: A core issue in crisis management is to extract from the mass of incoming information what is important for situational awareness during mass emergencies. Based on a case study we develop a prototypical application, TweetComp1, which is integrated into the decision-support component of a Tsunami early warning system and demonstrates the applicability of our approach. This paper describes four novel approaches using focused twitter crawling, trustworthiness analysis, geo-parsing, and multilingual tweet classification in the context of how they could be used for monitoring crises. The validity of our state-of-the art text mining and network analysis technologies will be verified in different experiments based on a human annotated gold standard corpus.
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Zijun Long, & Richard McCreadie. (2022). Is Multi-Modal Data Key for Crisis Content Categorization on Social Media? In Rob Grace, & Hossein Baharmand (Eds.), ISCRAM 2022 Conference Proceedings – 19th International Conference on Information Systems for Crisis Response and Management (pp. 1068–1080). Tarbes, France.
Abstract: The user-base of social media platforms, like Twitter, has grown dramatically around the world over the last decade. As people post everything they experience on social media, large volumes of valuable multimedia content are being recorded online, which can be analysed to help for a range of tasks. Here we specifically focus on crisis response. The majority of prior works in this space focus on using machine learning to categorize single-modality content (e.g. text of the posts, or images shared), with few works jointly utilizing multiple modalities. Hence, in this paper, we examine to what extent integrating multiple modalities is important for crisis content categorization. In particular, we design a pipeline for multi-modal learning that fuses textual and visual inputs, leverages both, and then classifies that content based on the specified task. Through evaluation using the CrisisMMD dataset, we demonstrate that effective automatic labelling for this task is possible, with an average of 88.31% F1 performance across two significant tasks (relevance and humanitarian category classification). while also analysing cases that unimodal models and multi-modal models success and fail.
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Zoha Sheikh, Hira Masood, Sharifullah Khan, & Muhammad Imran. (2017). User-Assisted Information Extraction from Twitter During Emergencies. In eds Aurélie Montarnal Matthieu Lauras Chihab Hanachi F. B. Tina Comes (Ed.), Proceedings of the 14th International Conference on Information Systems for Crisis Response And Management (pp. 684–691). Albi, France: Iscram.
Abstract: Disasters and emergencies bring uncertain situations. People involved in such situations look for quick answers to their rapid queries. Moreover, humanitarian organizations look for situational awareness information to launch relief operations. Existing studies show the usefulness of social media content during crisis situations. However, despite advances in information retrieval and text processing techniques, access to relevant information on Twitter is still a challenging task. In this paper, we propose a novel approach to provide timely access to the relevant information on Twitter. Specifically, we employee Word2vec embeddings to expand initial users queries and based on a relevance feedback mechanism we retrieve relevant messages on Twitter in real-time. Initial experiments and user studies performed using a real world disaster dataset show the significance of the proposed approach.
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