Oleg Aulov, Adam Price, & Milton Halem. (2014). AsonMaps: A platform for aggregation visualization and analysis of disaster related human sensor network observations. 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. 802–806). University Park, PA: The Pennsylvania State University.
Abstract: In this paper, we describe AsonMaps, a platform for collection, aggregation, visualization and analysis of near real-time, geolocated quantifiable information from a variety of heterogeneous social media outlets in order to provide emergency responders and other coordinating federal agencies not only with the means of listening to the affected population, but also to be able to incorporate this data into geophysical and probabilistic disaster forecast models that guide their response actions. Hurricane Sandy disaster is examined as a use-case scenario discussing the different types of quantifiable information that can be extracted from Instagram and Twitter.
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Benjamin Herfort, Melanie Eckle, & João Porto de Albuquerque. (2016). Being Specific about Geographic Information Crowdsourcing: A Typology and Analysis of the Missing Maps Project in South Kivu. 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: Recent development in disaster management and humanitarian aid is shaped by the rise of new information sources such as social media or volunteered geographic information. As these show great potential, making sense out of the new geographical datasets is a field of important scientific research. Therefore, this paper attempts to develop a typology of geographical information crowdsourcing. Furthermore, we use this typology to frame existing crowdsourcing projects and to further point out the potential of different kinds of crowdsourcing for disaster management and humanitarian aid. In order to exemplify its practical usage and value, we apply the typology to analyze the crowdsourcing methods utilized by the members of the Missing Maps project developed in South Kivu.
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Bonny Roos, Kim van Buul-Besseling, Jan-Willem Streefkerk, & Martijn Neef. (2015). Recover Faster from Disaster: Success Factors for a Crowdsourcing Platform. 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: In this paper, we present a model that identifies seven success factors for the development of crowdsourcing platforms for disaster recovery. This model integrates two existing theories. The first theory focuses on success factors of crowdsourcing initiatives in general. The second theory states how disaster relief operations can improve when they take the psychological components of resilience into account. By merging the core principles of these two theories and adding additional knowledge gained from literature study, we constructed an integrated success factor model for use in the development of crowdsourcing applications for disaster recovery. An initial validation of the success factor model was conducted within a case study on a crowdsourcing platform for disaster recovery which is currently being developed. Conclusions are drawn with regards to the applicability of the model to guide development of crowdsourcing platforms for disaster recovery.
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Dharma Dailey, & Kate Starbird. (2014). Visible skepticism: Community vetting after Hurricane Irene. 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. 777–781). University Park, PA: The Pennsylvania State University.
Abstract: Social media enable rapid, peer-to-peer information flow during crisis events, affordances that have both positive and negative consequences. The potential for spreading misinformation is a significant concern. Drawing on an empirical study of information-sharing practices in a crisis-affected community in the Catskill Mountains after Hurricane Irene, this paper describes how an ad hoc group of community members, led by a handful of journalists, employed specific work practices to mitigate misinformation. We illustrate how the group appropriated specific tools and performed visible skepticism, among other techniques, to help control the spread of false rumors. These findings suggest implications for the design of tools and the development of best practices for supporting community-led, crowd-powered response efforts during disasters.
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Denis Havlik, Jasmin Pielorz, & Adam Widera. (2016). Interaction with citizens experiments: from context-aware alerting to crowdtasking. 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 EU FP7 project DRIVER is conducting a number of experiments to assess the feasibility of addressing known deficiencies in crisis management. In this paper, we introduce experiments that investigate two-way communication solutions between crisis managers and citizens or unaffiliated volunteers. In the so-called ?Interaction with Citizens? experiments we are testing the usability and acceptance of the various methods and tools that facilitate crisis communication at several levels. This includes: informing and alerting of citizens; micro-tasking of volunteers; gathering of situational information about the crisis incident from volunteers; and usage of this information to improve situation awareness. At the time of writing this paper, our ?Interaction with Citizens? experiments are still under way. Therefore, this paper reports the lessons learned in the first two experiments along with the experimental setup and expectations for the final experiment.
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G.P. Jayasiri, & Raj Prasanna. (2023). Citizen Science for supporting Disaster Management Institutions in Sri Lanka. In V. L. Thomas J. Huggins (Ed.), Proceedings of the ISCRAM Asia Pacific Conference 2022 (pp. 77–88). Palmerston North, New Zealand: Massey Unversity.
Abstract: During 2016, 2017 and 2018, the country witnessed extreme rains which triggered flooding in several urban areas. The number of affected people by the 2018 floods was around 150,000 which shows a significant decrease compared to the events in 2016 and 2017. Several institutions provided their support via funding, relief, and rehabilitation mechanisms during these consecutive disasters. However, there are provisions which can further improve the performance of Disaster Management activities. Given this context, this study is carried out to investigate the application of citizen science concepts in several phases of Disaster Management in Sri Lanka. A scoping review supported by three case studies of floods was considered during the analysis. Limited participation of grass root level communities in decision-making and disaster planning, and issues related to data management are some of the main challenges identified in this study. Participatory mapping, Co-Design Projects, hackathons, and crowdfunding are some of the observed citizen science concepts which can be used to address the challenges and strengthen the Disaster Management activities in Sri Lanka. Further studies including interviews and questionnaire surveys were recommended to justify the findings.
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Lucy T. Gunawan, Siska Fitrianie, Willem-Paul Brinkman, & Mark A. Neerincx. (2012). Utilizing the potential of the affected population and prevalent mobile technology during disaster response: Propositions from a literature survey. 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: Despite the growing awareness of the untapped potential of the affected population in a disaster situation, their inclusion in a disaster management is extremely limited. This study aims to survey the literature to see whether utilizing the affected people and prevalent mobile technology can be used during disaster response. The idea is to provide the affected with a way to lead themselves to safety and empower them to serve as distributed active sources of information. This way, those people will reach safety by themselves, while at the same time helping to construct a clear image of the disaster situation without burdening the already overwhelmed emergency services. This study examines knowledge derived from disaster sociology, draws on experience from recent disasters, and extrapolates current technological solutions. By establishing that such a solution is feasible, it offers a basis for empirical studies on a mobile technology that can be used during disaster response. © 2012 ISCRAM.
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Holzhüter, M., Huhle, G., Reuter-Oppermann, M., Hellriegel, J., & Klafft, M. (2023). Acceptance study on application systems to improve situational incident management through bi-directional communication between citizens and decision-makers in emergencies and crises situations. In Jaziar Radianti, Ioannis Dokas, Nicolas Lalone, & Deepak Khazanchi (Eds.), Proceedings of the 20th International ISCRAM Conference (pp. 197–207). Omaha, USA: University of Nebraska at Omaha.
Abstract: Efficient hazard prevention and disaster control depend on situational awareness. Situational information is – among others – provided by citizens on the ground. Disaster managers are often reluctant to use such information on a large scale or in a systematic way for fear of being overwhelmed by information overload in a stressful crisis. New information technologies for crisis management are strongly dependent on the acceptance of the people using them and can only be successful as socio-technical systems. Therefore, 354 employees of public and private emergency operation centres as well as members of crisis management teams were asked to assess different information sharing technologies. 504 people from the public responded to an online survey about their willingness to use such technologies. The results indicate a high level of acceptance by both user groups for bi directional communication technologies for situation management and the improvement of situational awareness.
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Johannes Anhorn, Benjamin Herfort, & João Porto de Albuquerque. (2016). Crowdsourced Validation and Updating of Dynamic Features in OpenStreetMap – An analysis of Shelter Mapping after the 2015 Nepal Earthquake. 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 paper presents results from a validation process of OpenStreetMap (OSM) rapid mapping activities using crowdsourcing technology in the aftermath of the Gorkha earthquake 2015 in Nepal. We present a framework and tool to iteratively validate and update OSM objects. Two main objectives are addressed: first, analyzing the accuracy of the volunteered geographic information (VGI) generated by the OSM community; second, investigating the spatio-temporal dynamics of spontaneous shelter camps in Kathmandu. Results from three independent validation iterations show that only 10 % of the OSM objects are false positives (no shelter camps). Unexpectedly, previous mapping experience only had a minor influence on mapping accuracy. The results further show that it is critical to monitor the temporal dynamics. Out of 4,893 identified shelter camps, 54% were already empty/closed six days after the first mapping. So far, updating geographical features during humanitarian crisis is not properly addressed by the existing crowdsourcing approaches.
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Ulrich Meissen, & Frank Fuchs-Kittowski. (2014). Towards a reference architecture of crowdsourcing integration in early warning systems. In and P.C. Shih. L. Plotnick M. S. P. S.R. Hiltz (Ed.), ISCRAM 2014 Conference Proceedings – 11th International Conference on Information Systems for Crisis Response and Management (pp. 334–338). University Park, PA: The Pennsylvania State University.
Abstract: Crowdsourcing has the potential to become a crucial information source in disaster management. In order to become effective as an integrated part of disaster management systems it is important to set the general architectural foundations for such integrations beyond prototypical experiments. This paper discusses general architectural principles of the application of crowdsourcing in Early Warning Systems (EWS). An integrated architecture is proposed to use classical sensor data and crowdsourcing in an EWS solution. Therefore, typical components of crowdsourcing applications are identified and mapped to monitoring subsystems of EWS's. Three main structural variants of applying crowdsourcing in early warning systems along the example of a prototypical extension of two existing large-scale hydro-meteorological warning systems are presented.
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Mohammed Benali, A. R. G. (2017). Towards a Crowdsourcing-based Approach to enhance Decision Making in Collaborative Crisis Management. 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. 554–563). Albi, France: Iscram.
Abstract: Managing crises is considered as one of the most complicated organizational and managerial task. Indeed, dealing with such situations calls for many groups from different institutions and organizations to interact and collaborate their efforts in a timely manner to reduce their effects. However, response organizations are challenged by several problems. The urgent need of a shared and mutual situational awareness, information and knowledge about the situation are distributed across time and space and owned by both organizations and people. Additionally, decisions and actions have to be achieved promptly, under stress and time pressure. The contribution outlined in this paper is suggesting a crowdsourcing-based approach for decision making in collaborative crisis management based on the literature requirements. The objective of the approach is to support situational awareness and enhance the decision making process by involving citizens in providing opinions and evaluations of potential response actions.
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Nick LaLone, Andrea H. Tapia, Nathan A. Case, Elizabeth MacDonald, Michelle Hall, & Matt Heavner. (2015). HYBRID COMMUNITY PARTICIPATION IN CROWDSOURCED EARLY WARNING SYSTEMS. 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: In this paper we present Aurorasaurus: a website, a mobile application, and a citizen science initiative that allows a community of users to report and verify sightings of the Aurora Borealis. Through ad-hoc data indirectly offered through social media, a community of citizen scientists verify sightings of the Aurora Borealis. These verified data are tested against currently existing aurora-forecasting models. The insights these data provide are transformed into map and text-based forms. In addition, notifications are sent to interested participants in a timely manner. This is a design test-bed for an early warning system (EWS) that is capable of detecting and communicating the earliest signs of disaster to community members in near real time. Most importantly, this system incorporates community participation in improving the quality of data mined from Twitter and direct community contributions.
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Pestana, M. C., Vieira, V., & Ribeiro, A. (2023). Crowdsourcing and collaboration for crisis communication: a systematic review. In Jaziar Radianti, Ioannis Dokas, Nicolas Lalone, & Deepak Khazanchi (Eds.), Proceedings of the 20th International ISCRAM Conference (p. 1072). Omaha, USA: University of Nebraska at Omaha.
Abstract: Establishing collaborative communication in crisis solutions provides appropriate support and efficient response to the public when an emergency scenario appears. The public comprises a crowd of humans involved in their quotidian activities. Communication should flow collaboratively between operational centers, civils, and public institutions professionals. Crowdsourcing is a technique that supports communication between the diverse public by using people collaboration. This paper’s primary goal is to study the state-of-the-art regarding crowdsourcing and collaboration for crisis communication. A systematic literature review guided this study. As a result, 20 papers have been selected about solutions that support communication for crises in the last ten years. Findings reveal solutions whose requirements provide rapid emergency response, good coordination between the agents and the crowd, and trustful data passing through a validation process.
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Quynh Nhu Nguyen, Antonella Frisiello, & Claudio Rossi. (2019). The Design of a Mobile Application for Crowdsourcing in Disaster Risk Reduction. 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: Disaster Risk Reduction is a complex field in which a huge amount of data is collected and processed every day
in order to plan and run preparedness and response actions, which are required to get ready and to effectively
respond to natural disasters when they strike. This paper, which targets a wide audience, focuses on the design of
a mobile application that aims to integrate the crowdsourcing paradigm in current Disaster Risk Reduction
processes. The design process is integrated in the User Centred Approach, which we apply through a co-design
methodology involving end-users, iterative prototyping and development phases, and five in-field evaluations of
the implemented solution. We describe both the design activities and the results obtained from end-users�
feedbacks focusing on the perspective of first responders.
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Rémy Bossu, Robert Steed, Gilles Mazet-Roux, Caroline Etivant, & Fréderic Roussel. (2015). THE EMSC TOOLS USED TO DETECT AND DIAGNOSE THE IMPACT OF GLOBAL EARTHQUAKES FROM DIRECT AND INDIRECT EYEWITNESSES? CONTRIBUTIONS. 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: This paper presents the strategy and operational tools developed and implemented at the Euro-Mediterranean Seismological Centre (EMSC) to detect and diagnose the impact of global earthquakes within minutes by combining « flashsourcing » (real time monitoring of website traffic) with social media monitoring and crowdsourcing.
This approach serves both the seismological community and the public and can contribute to improved earthquake response. It collects seismological observations, improves situation awareness from a few tens of seconds to a couple of hours after earthquake occurrence and is the basis of innovative targeted real time public information services.
We also show that graphical input methods can improve crowdsourcing tools both for the increasing use of mobile devices and to erase language barriers. Finally we show how social network harvesting could provide information on indirect earthquake effects such as triggered landslides and fires, which are difficult to predict and monitor through existing geophysical networks.
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Sara Barozzi, Jose Luis Fernandez Marquez, Amudha Ravi Shankar, & Barbara Pernici. (2019). Filtering images extracted from social media in the response phase of emergency events. 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: The use of social media to support emergency operators in the first hours of the response phases can improve the
quality of the information available and awareness on ongoing emergency events. Social media contain both textual
and visual information, in the form of pictures and videos. The problem related to the use of social media posts
as a source of information during emergencies lies in the difficulty of selecting the relevant information among
a very large amount of irrelevant information. In particular, we focus on the extraction of images relevant to an
event for rapid mapping purpose. In this paper, a set of possible filters is proposed and analyzed with the goal of
selecting useful images from posts and of evaluating how precision and recall are impacted. Filtering techniques,
which include both automated and crowdsourced steps, have the goal of providing better quality posts and easy
manageable data volumes both to emergency responders and rapid mapping operators. The impact of the filters on
precision and recall in extracting relevant images is discussed in the paper in two different case studies.
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Axel Schulz, Heiko Paulheim, & Florian Probst. (2012). Crisis information management in the Web 3.0 age. 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: The effectiveness of emergency response largely depends on having a precise, up-to-date situational picture. With the World Wide Web having evolved from a small read-only text collection to a large-scale collection of socially created data accessible both to machines and humans alike, with the advent of social media and ubiquitous mobile applications, new sources of information are available. Currently, that potentially valuable information remains mostly unused by the command staff, mainly because the sheer amount of information cannot be handled efficiently. In this paper, we show an approach for turning massive amounts of unstructured citizen-generated content into relevant information supporting the command staff in making better informed decisions. We leverage Linked Open Data and crowdsourcing for processing data from social media, and we show how the combination of human intelligence in the crowd and automatic approaches for enhancing the situational picture with Linked Open Data will lead to a Web 3.0 approach for more efficient information handling in crisis management. © 2012 ISCRAM.
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Sofia Eleni Spatharioti, & Seth Cooper. (2017). On Variety, Complexity, and Engagement in Crowdsourced Disaster Response Tasks. 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. 489–498). Albi, France: Iscram.
Abstract: Crowdsourcing is used to enlist workers as a resource for a variety of applications, including disaster response. However, simple tasks such as image labeling often feel monotonous and lead to worker disengagement. This provides a challenge for designing successful crowdsourcing systems. Existing research in the design of work indicates that task variety is a key factor in worker motivation. Therefore, we asked Amazon Mechanical Turk workers to complete a series of disaster response related subtasks, consisting of either image labeling or locating photographed areas on a map. We varied the frequency at which workers encountered the dierent subtask types, and found that switching subtask type at dierent frequencies impacted measures of worker engagement. This indicates that a certain amount of variety in subtasks may engage crowdsourcing workers better than uniform subtask types.
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Sofia Eleni Spatharioti, Rebecca Govoni, Jennifer S. Carrera, Sara Wylie, & Seth Cooper. (2017). A Required Work Payment Scheme for Crowdsourced Disaster Response: Worker Performance and Motivations. In eds Aurélie Montarnal Matthieu Lauras Chihab Hanachi F. B. Tina Comes (Ed.), Proceedings of the 14th International Conference on Iformation Systems for Crisis Response And Management (pp. 475–488). Albi, France: Iscram.
Abstract: Crowdsourcing is an increasingly popular approach for processing data in response to disasters. While volunteer crowdsourcing may suÿce for high-profile disasters, paid crowdsourcing may be necessary to recruit workers for less prominent events. Thus, understanding the impact of payment schemes on worker behavior and motivation may improve outcomes. In this work, we presented workers recruited from Amazon Mechanical Turk with a disaster response task in which they could provide a variable number of image ratings. We paid workers a fixed amount to provide a minimum number of image ratings, allowing them to voluntarily provide more if desired; this allowed us to examine the impact of dierent amounts of required work. We found that requiring no ratings resulted in workers voluntary completing more work, and being more likely to indicate motivation related to interest on a post survey, than when small numbers of ratings were required. This is consistent with the motivational crowding-out eect, even in paid crowdsourcing. We additionally found that providing feedback on progress positively impacted the amount of work done.
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Sofia Eleni Spatharioti, Sara Wylie, & Seth Cooper. (2018). Does Flight Path Context Matter? Impact on Worker Performance in Crowdsourced Aerial Imagery Analysis. In Kees Boersma, & Brian Tomaszeski (Eds.), ISCRAM 2018 Conference Proceedings – 15th International Conference on Information Systems for Crisis Response and Management (pp. 621–628). Rochester, NY (USA): Rochester Institute of Technology.
Abstract: Natural disasters result in billions of dollars in damages annually and communities left struggling with the difficult task of response and recovery. To this end, small private aircraft and drones have been deployed to gather images along flight paths over the affected areas, for analyzing aerial photography through crowdsourcing. However, due to the volume of raw data, the context and order of these images is often lost when reaching workers. In this work, we explored the effect of contextualizing a labeling task on Amazon Mechanical Turk, by serving workers images in the order they were collected on the flight and showing them the location of the current image on a map. We did not find a negative impact from the loss of contextual information, and found map context had a negative impact on worker performance. This may indicate that ordering images based on other criteria may be more effective.
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Sofia Eleni Spatharioti, Sara Wylie, & Seth Cooper. (2018). Identifying and Assessing Points of Interest through Crowdsourced Image Analysis. In Kees Boersma, & Brian Tomaszeski (Eds.), ISCRAM 2018 Conference Proceedings – 15th International Conference on Information Systems for Crisis Response and Management (pp. 1123–1125). Rochester, NY (USA): Rochester Institute of Technology.
Abstract: During a natural disaster, major damages to critical structures such as bridges or power lines can severely disrupt community functions for long periods of time, making the task of swiftly identifying this type of damage vital for response and recovery. However, survey flight paths are often designed with a main focus of complete and quick coverage of affected areas through aerial photography, which is then assigned to volunteers to aid in damage report and labeling. We designed a crowdsourcing interface that focuses on locating points of interest and assessing damage using images from survey flights. We tested our design using a disaster and a non-disaster application by recruiting volunteers on Amazon Mechanical Turk. We found that the type of structure may cause difficulties for crowd workers in providing accurate assessments and that designing flights to also target structures may provide higher quality imagery for this type of task.
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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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Therese Habig, Richard Lüke, Simon Gehlhar, Torben Sauerland, & Daniel Tappe. (2021). A Consolidated Understanding of Disaster Community Technologies. 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. 778–791). Blacksburg, VA (USA): Virginia Tech.
Abstract: Since the beginning of this millennium, there has been an increasing use of social media and crowdsourcing (SMCS) technologies in disaster situations (Reuter & Kaufhold, 2018). Disaster management organizations and corresponding research are increasingly working on ways of integrating SMCS into the processes of crisis management. In a changing technological landscape to address disasters, and with increasing diversity of stakeholders in disasters, the purpose of this research is to provide an overview of technologies for SMCS within disasters to improve community resilience. The identified and analyzed technologies are summarized under the term “Disaster Community Technologies” (DCT). The paper presents a classification schema (the “DCT-schema”) for those technologies. The goal is to generate an overview of DCT in a rapidly evolving environment and to provide the practical benefit for different stakeholders to identify the right one from the overview.
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Ulrich Meissen, Frank Fuchs-Kittowski, Michael Jendreck, Stefan Pfennigschmidt, Markus Hardt, & Agnès Voisard. (2017). A general system architecture and design for the coordination of volunteers for agile disaster response. 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. 890–900). Albi, France: Iscram.
Abstract: In the recent decade the evolvement and widespread success of new technologies in particular in the field of computing power, network bandwidth, mobile networks and wearable devices have prepared the foundation for completely new approaches in crisis management. Currently, we are at the edge that such new technologies for crisis management are becoming a real and practically applicable option, e.g. in the field of alerting, crowdsourcing, and crowdtasking. In parallel, we witness in the recent years that citizens are more and more willing to help during crisis and disasters, thus providing a large – yet unused – potential for agile support in disaster preparation and response. In many disaster situations the emergency personnel reach the limits of their capabilities. In particular during the isolation phase the support of such volunteers can be a valuable benefit for disaster response. With the help of new technologies crisis management can provide current on-site information via mobile devices in real time as well as organize and coordinate the activities of the volunteers at specific locations. In this paper we present the results of the research project ENSURE: a general architecture and a system design for the coordination of spontaneous volunteers for agile disaster response. With the expected broader implementation of such systems in disaster management in the future it is inevitable to elaborate such common technological foundations for practical mass applications.
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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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