|
|
Amanda Hughes, Keri Stephens, Steve Peterson, Hemant Purohit, Anastazja G. Harris, Yasas Senarath, et al. (2022). Human-AI Teaming for COVID-19 Response: A Practice & Research Collaboration Case Study. In Rob Grace, & Hossein Baharmand (Eds.), ISCRAM 2022 Conference Proceedings – 19th International Conference on Information Systems for Crisis Response and Management (pp. 1048–1057). Tarbes, France.
Abstract: Practice and research collaborations in the disaster domain have the potential to improve emergency management practices while also advancing disaster science theory. However, they also pose challenges as practitioners and researchers each have their own culture, history, values, incentives, and processes that do not always facilitate collaboration. In this paper, we reflect on a 6-month practice and research collaboration, where researchers and practitioners worked together to craft a social media monitoring system for emergency managers in response to the COVID-19 pandemic. The challenges we encountered in this project fall into two broad categories, job-related and timescale challenges. Using prior research on team science as a guide, we discuss several challenges we encountered in these two categories and show how our team sought to overcome them. We conclude with a set of best practices for improving practice and research collaborations.
|
|
|
|
Muhammad Imran, Firoj Alam, Umair Qazi, Steve Peterson, & Ferda Ofli. (2020). Rapid Damage Assessment Using Social Media Images by Combining Human and Machine Intelligence. 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. 761–773). Blacksburg, VA (USA): Virginia Tech.
Abstract: Rapid damage assessment is one of the core tasks that response organizations perform at the onset of a disaster to understand the scale of damage to infrastructures such as roads, bridges, and buildings. This work analyzes the usefulness of social media imagery content to perform rapid damage assessment during a real-world disaster. An automatic image processing system, which was activated in collaboration with a volunteer response organization, processed ~280K images to understand the extent of damage caused by the disaster. The system achieved an accuracy of 76% computed based on the feedback received from the domain experts who analyzed ~29K system-processed images during the disaster. An extensive error analysis reveals several insights and challenges faced by the system, which are vital for the research community to advance this line of research.
|
|
|
|
Steve Peterson. (2016). More Research Needed on the Concurrent Usage of Information Systems during Emergencies. 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: This abstract highlights research challenges to improving effectiveness of integrating information and communication technologies during emergencies. Proposed as a research focus is the integration of proven virtual activation processes with an unobtrusive research presence. This positions the research presence during a real-time emergency to glean previously unknown information/rationales on how decision-makers decide and take action. Establishing a collaborative partnership by combining a ?research presence? with the ?virtual operation capability,? is essential. Mutual understanding must embrace the precept of no disruption to first responders in actual response and recovery efforts. Consensus should be reached in identifying measurable outcomes for the research. The collaborative effort opens a groundbreaking area for consideration of study in crisis response and management. It would shed new light on an underexplored, critical area of emergency management and has the potential to further enhance the value of information and communication systems in preparing, responding, and recovering from emergencies.
|
|
|
|
Steve Peterson, Chris Thompson, & Cat Graham. (2018). Getting Disaster Data Right: A Call for Real-time Research in Disaster Response. In Kees Boersma, & Brian Tomaszeski (Eds.), ISCRAM 2018 Conference Proceedings – 15th International Conference on Information Systems for Crisis Response and Management (pp. 851–859). Rochester, NY (USA): Rochester Institute of Technology.
Abstract: In the response phase of disasters, minimal research has been conducted on the near real-time operational usage of social media. Research findings during this phase could provide evidence to the emergency management community that social media content can be retrieved, verified, and ultimately utilized in decision-making. This paper discusses potential strategies for conducting future research in near real-time during disasters to gain insightful knowledge rarely captured. Following the April 25, 2015, magnitude 7.8 Nepal earthquake, a team of 20 digital volunteers were virtually activated for 48 hours to extract medical-related information from multiple social media platforms and Internet sources. This practitioner insight paper examines methods applied to filter, classify, analyze, verify, and distribute the medical-related information in a timely manner. Association of past research studies are applied to the digital volunteer's experience within a case study framework, calling attention to the feasibility of digital volunteers as an information source in future research.
|
|
|
|
Steve Peterson, & Denis Gusty. (2018). Incorporating Digital Volunteers into Exercises: A Case Study on CAUSE V. In Kees Boersma, & Brian Tomaszeski (Eds.), ISCRAM 2018 Conference Proceedings – 15th International Conference on Information Systems for Crisis Response and Management (pp. 1126–1129). Rochester, NY (USA): Rochester Institute of Technology.
Abstract: The U.S. Department of Homeland Security (DHS) Science and Technology Directorate (S&T) and Canada Department of National Defence's Centre for Security Science conducted its fifth Canada-U.S. Enhanced Resiliency Experiment (CAUSE V) on November 15 – 16, 2017 along the border between the Canadian province of British Columbia and the state of Washington. The experiment tested emerging technologies to promote more effective communication and information sharing for emergency management officials and first responder agencies on both sides of the border in response to a Mt. Baker volcanic eruption and lahar mudflow scenario. The CAUSE V experiment explored the use of trained digital volunteers to provide operational and public information support to emergency management professionals. These digital volunteers were assigned to monitor simulated social media platforms, identifying information according to pre-assigned mission assignments, including misinformation and rumor control, and reporting this information to emergency management officials and first responder agencies. Researchers from the University of Washington were in attendance to specifically observe the efforts of the digital volunteers during the experiment. Research observations, and the benefits of integrating the research and practitioner communities, will be highlighted on the poster.
|
|
|
|
Steve Peterson, Keri Stephens, Hemant Purohit, & Amanda Hughes. (2019). When Official Systems Overload: A Framework for Finding Social Media Calls for Help during Evacuations. 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: During large-scale disasters it is not uncommon for Public Safety Answering Points (e.g., 9-1-1) to encounter
service disruptions or become overloaded due to call volume. As observed in the two past United States hurricane
seasons, citizens are increasingly turning to social media whether as a consequence of their inability to reach
9-1-1, or as a preferential means of communications. Relying on past research that has examined social media
use in disasters, combined with the practical knowledge of the first-hand disaster response experiences, this paper
develops a knowledge-driven framework containing parameters useful in identifying patterns of shared
information on social media when citizens need help. This effort explores the feasibility of determining
differences, similarities, common themes, and time-specific discoveries of social media calls for help associated
with hurricane evacuations. At a future date, validation of this framework will be demonstrated using datasets
from multiple disasters. The results will lead to recommendations on how the framework can be modified to make
it applicable as a generic disaster-type characterization tool.
|
|
|
|
Valerio Lorini, Carlos Castillo, Steve Peterson, Paola Rufolo, Hemant Purohit, Diego Pajarito, et al. (2021). Social Media for Emergency Management: Opportunities and Challenges at the Intersection of Research and Practice. 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. 772–777). Blacksburg, VA (USA): Virginia Tech.
Abstract: This paper summarizes key opportunities and challenges identified during the workshop “Social Media for Disaster Risk Management: Researchers Meet Practitioners” which took place online in November 2020. It constitutes a work-in-progress towards identifying new directions for research and development of systems that can better serve the information needs of emergency managers. Practitioners widely recognize the potential of accessing timely information from social media. Nevertheless, the discussion outlined some critical challenges for improving its adoption during crises. In particular, validating such information and integrating it with authoritative information and into more traditional information systems for emergency managers requires further work, and the negative impacts of misinformation and disinformation need to be prevented.
|
|
