| Records |
Author  |
Viktor Sköld Gustafsson; Tobias Andersson Granberg; Sofie Pilemalm; Martin Waldemarsson |
| Title |
Managing Natural Hazards in Sweden – Needs for Improved Information and Decision Support Systems |
Type |
Conference Article |
| Year |
2022 |
Publication |
ISCRAM 2022 Conference Proceedings – 19th International Conference on Information Systems for Crisis Response and Management |
Abbreviated Journal |
Iscram 2022 |
| Volume |
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Issue |
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Pages |
376-384 |
| Keywords |
Emergency response; extreme weather events; command and control; needs analysis |
| Abstract |
This paper explores opportunities for information systems to support emergency response to multiple natural hazards. Interviews were conducted with 12 representatives from actors of the Swedish emergency response system about response to multiple natural hazards. Challenges and needs connected to five themes influencing the response effort were identified: Cooperation, Resource management, Command and control, Common operational picture, and Risk management. The results illuminate a lack of technology to support decisions and analyses during emergency response to both single and multiple natural hazards. Based on this, the paper suggests and discusses information systems and decision support tools to assist in satisfying the identified needs. The findings can inform policy makers in emergency response of where to concentrate the development of collaborative preparedness and response work, and the scientific community of future research directions. |
| Address |
Linköping University; University of Agder |
| Corporate Author |
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Thesis |
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| Publisher |
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Place of Publication |
Tarbes, France |
Editor |
Rob Grace; Hossein Baharmand |
| Language |
English |
Summary Language |
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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 |
978-82-8427-099-9 |
Medium |
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| Track |
Command and Control Studies |
Expedition |
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Conference |
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| Notes |
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Approved |
no |
| Call Number |
ISCRAM @ idladmin @ |
Serial |
2425 |
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| Author |
Zijun Long; Richard McCreadie |
| Title |
Is Multi-Modal Data Key for Crisis Content Categorization on Social Media? |
Type |
Conference Article |
| Year |
2022 |
Publication |
ISCRAM 2022 Conference Proceedings – 19th International Conference on Information Systems for Crisis Response and Management |
Abbreviated Journal |
Iscram 2022 |
| Volume |
|
Issue |
|
Pages |
1068-1080 |
| Keywords |
Social Media Classification; Multi-modal Learning; Crisis Management; Deep Learning, BERT; Supervised Learning |
| 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. |
| Address |
University of Glasgow; University of Glasgow |
| Corporate Author |
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Thesis |
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| Publisher |
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Place of Publication |
Tarbes, France |
Editor |
Rob Grace; Hossein Baharmand |
| Language |
English |
Summary Language |
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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 |
978-82-8427-099-9 |
Medium |
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| Track |
Social Media for Crisis Management |
Expedition |
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Conference |
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| Notes |
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Approved |
no |
| Call Number |
ISCRAM @ idladmin @ |
Serial |
2472 |
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