| Records |
Author  |
Andrea H. Tapia; Kartikeya Bajpai; Bernard J. Jansen; John Yen |
| Title |
Seeking the trustworthy tweet: Can microblogged data fit the information needs of disaster response and humanitarian relief organizations |
Type |
Conference Article |
| Year |
2011 |
Publication |
8th International Conference on Information Systems for Crisis Response and Management: From Early-Warning Systems to Preparedness and Training, ISCRAM 2011 |
Abbreviated Journal |
ISCRAM 2011 |
| Volume |
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Issue |
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Pages |
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| Keywords |
Disasters; Information systems; Public relations; Humanitarian; Microblogging; Ngo; Relief; Trust; Twitter; Emergency services |
| Abstract |
Message data has, as yet, not been adopted by large-scale, international humanitarian relief organizations in an instrumental fashion. While the largest of these organizations have adopted messaging as part of their Public Relations functions, few have used any form of message data originating in the field, at the time of disaster. The message data being contributed by bystanders and those affected by a disaster, as it is happening, has largely been deemed as unverifiable and untrustworthy, and thus construed as unsuitable for incorporation into established mechanisms for organizational decision-making. In this paper, we describe the discursive barriers to the use of microblogged data by Humanitarian NGOs during times of disaster. We present data and findings from a study involving representatives from thirteen humanitarian organizations. Our analysis suggests that the organizational barriers, both in terms of function and structure, and the data itself, form barriers to organizational use of microblogged data. We propose three socio-technical solutions to surpassing adoption bottlenecks, namely bounded microblogging, microblogged data as contextual data, and/or use of computational solutions. |
| Address |
Pennsylvania State University, United States |
| Corporate Author |
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Thesis |
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| Publisher |
Information Systems for Crisis Response and Management, ISCRAM |
Place of Publication |
Lisbon |
Editor |
M.A. Santos, L. Sousa, E. Portela |
| Language |
English |
Summary Language |
English |
Original Title |
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| Series Editor |
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Series Title |
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Abbreviated Series Title |
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| Series Volume |
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Series Issue |
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Edition |
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| ISSN |
2411-3387 |
ISBN |
9789724922478 |
Medium |
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| Track |
Humanitarian Challenges |
Expedition |
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Conference |
8th International ISCRAM Conference on Information Systems for Crisis Response and Management |
| Notes |
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Approved |
no |
| Call Number |
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Serial |
991 |
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| Author |
Cornelia Caragea; Nathan McNeese; Anuj Jaiswal; Greg Traylor; Hyun-Woo Kim; Prasenjit Mitra; Dinghao Wu; Andrea H. Tapia; Lee Giles; Bernard J. Jansen; John Yen |
| Title |
Classifying text messages for the haiti earthquake |
Type |
Conference Article |
| Year |
2011 |
Publication |
8th International Conference on Information Systems for Crisis Response and Management: From Early-Warning Systems to Preparedness and Training, ISCRAM 2011 |
Abbreviated Journal |
ISCRAM 2011 |
| Volume |
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Issue |
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Pages |
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| Keywords |
Abstracting; Artificial intelligence; Disaster prevention; Information systems; Learning systems; Text processing; Disaster relief; Emergency response; Emergency situation; Haiti earthquakes; Information technology infrastructure; Nongovernmental organizations; Relief workers; Self-organizing behavior; Earthquakes |
| Abstract |
In case of emergencies (e.g., earthquakes, flooding), rapid responses are needed in order to address victims' requests for help. Social media used around crises involves self-organizing behavior that can produce accurate results, often in advance of official communications. This allows affected population to send tweets or text messages, and hence, make them heard. The ability to classify tweets and text messages automatically, together with the ability to deliver the relevant information to the appropriate personnel are essential for enabling the personnel to timely and efficiently work to address the most urgent needs, and to understand the emergency situation better. In this study, we developed a reusable information technology infrastructure, called Enhanced Messaging for the Emergency Response Sector (EMERSE), which classifies and aggregates tweets and text messages about the Haiti disaster relief so that non-governmental organizations, relief workers, people in Haiti, and their friends and families can easily access them. |
| Address |
College of Information Sciences and Technology, Pennsylvania State University, University Park, PA-16801, United States |
| Corporate Author |
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Thesis |
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| Publisher |
Information Systems for Crisis Response and Management, ISCRAM |
Place of Publication |
Lisbon |
Editor |
M.A. Santos, L. Sousa, E. Portela |
| Language |
English |
Summary Language |
English |
Original Title |
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| Series Editor |
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Series Title |
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Abbreviated Series Title |
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| Series Volume |
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Series Issue |
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Edition |
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| ISSN |
2411-3387 |
ISBN |
9789724922478 |
Medium |
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| Track |
Analytical Information Systems |
Expedition |
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Conference |
8th International ISCRAM Conference on Information Systems for Crisis Response and Management |
| Notes |
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Approved |
no |
| Call Number |
|
Serial |
371 |
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| Author |
Guruprasad Airy; Tracy Mullen; John Yen |
| Title |
Market based adaptive resource allocation for distributed rescue teams |
Type |
Conference Article |
| Year |
2009 |
Publication |
ISCRAM 2009 – 6th International Conference on Information Systems for Crisis Response and Management: Boundary Spanning Initiatives and New Perspectives |
Abbreviated Journal |
ISCRAM 2009 |
| Volume |
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Issue |
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Pages |
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| Keywords |
Information systems; Planning; Adaptive resource allocations; Combinatorial auction; Limited information; Multi agent; Multi-agent planning; Resource assignment; Resource requirements; System's performance; Resource allocation |
| Abstract |
The dynamic nature of real-world rescue scenarios (e.g., military, emergency first response, hurricane relief) requires constant reevaluation of resource assignments. New events can trigger additional resource requirements generating conflicts about how to reassign resources across tasks in an emerging crisis. Reallocation is further complicated as some resources are synergistic (i.e., helicopter and pilot) and many distributed rescue teams have limited information about other teams' status. We show how integrating a team-based multi-agent planning system with standard combinatorial auction methods to dynamically re-allocate resources can maximize overall rescue utility while providing for graceful managed degradation under conditions of extreme stress. The key innovation of our approach is that we explicitly provide a framework that incorporates the costs involved in dynamically switching resources from one task to another. We compare our system's performance against two other approaches. |
| Address |
Pennsylvania State University, United States |
| Corporate Author |
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Thesis |
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| Publisher |
Information Systems for Crisis Response and Management, ISCRAM |
Place of Publication |
Gothenburg |
Editor |
J. Landgren, S. Jul |
| Language |
English |
Summary Language |
English |
Original Title |
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| Series Editor |
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Series Title |
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Abbreviated Series Title |
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| Series Volume |
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Series Issue |
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Edition |
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| ISSN |
2411-3387 |
ISBN |
9789163347153 |
Medium |
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| Track |
Intelligent Systems |
Expedition |
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Conference |
6th International ISCRAM Conference on Information Systems for Crisis Response and Management |
| Notes |
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Approved |
no |
| Call Number |
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Serial |
259 |
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