Articles | Volume 21, issue 5
https://doi.org/10.5194/nhess-21-1431-2021
© Author(s) 2021. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Special issue:
https://doi.org/10.5194/nhess-21-1431-2021
© Author(s) 2021. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Review article
| 
06 May 2021
Review article |
| 06 May 2021
| 06 May 2021
Opportunities and risks of disaster data from social media: a systematic review of incident information
Matti Wiegmann
CORRESPONDING AUTHOR
Bauhaus-Universität Weimar, Web Technology and Information Systems Group, Weimar, Germany
German Aerospace Center (DLR), Institute of Data Science, Jena, Germany
Jens Kersten
German Aerospace Center (DLR), Institute of Data Science, Jena, Germany
Hansi Senaratne
German Aerospace Center (DLR), German Remote Sensing Data Center, Oberpfaffenhofen, Germany
Martin Potthast
Leipzig University, Text Mining and Retrieval Group, Leipzig, Germany
Friederike Klan
German Aerospace Center (DLR), Institute of Data Science, Jena, Germany
Benno Stein
Bauhaus-Universität Weimar, Web Technology and Information Systems Group, Weimar, Germany
Viewed
Total article views: 6,389 (including HTML, PDF, and XML)
Cumulative views and downloads
(calculated since 17 Jul 2020)
| HTML | XML | Total | BibTeX | EndNote | |
|---|---|---|---|---|---|
| 5,037 | 1,221 | 131 | 6,389 | 191 | 160 |
- HTML: 5,037
- PDF: 1,221
- XML: 131
- Total: 6,389
- BibTeX: 191
- EndNote: 160
Total article views: 5,661 (including HTML, PDF, and XML)
Cumulative views and downloads
(calculated since 06 May 2021)
| HTML | XML | Total | BibTeX | EndNote | |
|---|---|---|---|---|---|
| 4,699 | 847 | 115 | 5,661 | 159 | 132 |
- HTML: 4,699
- PDF: 847
- XML: 115
- Total: 5,661
- BibTeX: 159
- EndNote: 132
Total article views: 728 (including HTML, PDF, and XML)
Cumulative views and downloads
(calculated since 17 Jul 2020)
| HTML | XML | Total | BibTeX | EndNote | |
|---|---|---|---|---|---|
| 338 | 374 | 16 | 728 | 32 | 28 |
- HTML: 338
- PDF: 374
- XML: 16
- Total: 728
- BibTeX: 32
- EndNote: 28
Viewed (geographical distribution)
Total article views: 6,389 (including HTML, PDF, and XML)
Thereof 6,152 with geography defined
and 237 with unknown origin.
Total article views: 5,661 (including HTML, PDF, and XML)
Thereof 5,415 with geography defined
and 246 with unknown origin.
Total article views: 728 (including HTML, PDF, and XML)
Thereof 728 with geography defined
and 0 with unknown origin.
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| Country | # | Views | % |
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| Total: | 0 |
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Cited
18 citations as recorded by crossref.
- A Citizen Science Approach for Analyzing Social Media With Crowdsourcing C. Bono et al.
- Review article: Detection of actionable tweets in crisis events A. Kruspe et al.
- Towards a study of everyday geographic information: Bringing the everyday into view S. De Sabbata et al.
- Integrating social media data and machine learning methods for flash flood susceptibility mapping in China Y. Zhuang et al.
- A multimodal GeoAI approach to combining text with spatiotemporal features for enhanced relevance classification of social media posts in disaster response D. Hanny et al.
- R2D-EQ: a two-stage workflow for risk reasoning and decision-making in earthquake emergency scenarios L. Yao et al.
- AFAD Akreditasyon Sistemi’ne Başvuru Yapan Bir Kuruluşta Kentsel Arama Kurtarma Ekibi için Personel Seçimi T. Danışan & T. Eren
- What to do if there’s a nuclear attack? A quality and readability analysis of websites Y. Solak et al.
- Insurance as an Alternative for Sustainable Economic Recovery after Natural Disasters: A Systematic Literature Review . Kalfin et al.
- “Generalization of convolutional network to domain adaptation network for classification of disaster images on twitter” A. Khattar & S. Quadri
- Pathways to Socially Sustainable Adaptation: Real-Time and Context-Specific Vulnerability Assessment in South Carolina after Hurricane Dorian M. Batouli & D. Joshi
- HiDEF: A Hierarchical Disaster Information Extraction Framework Based on Adversarial Augmentation and Dynamic Prompting X. Wang et al.
- Quantifying socioeconomic impacts of urban pluvial flooding using social media and SDGSAT-1 nighttime light data: A case study of Kunming, China X. Zhang et al.
- The utility of using Volunteered Geographic Information (VGI) for evaluating pluvial flood models M. Drews et al.
- Environmental safety in the digital age: new methods and approaches E. Shchekotin
- The movement pattern changes of population following a disaster: Example of the Aegean Sea earthquake of October 2020 C. Varol et al.
- Shuiyuan DPT: a disaster management tool for a disaster resilient community M. Tsai et al.
- #RecoverSouthCoast: how Twitter can support and hinder recovery R. Ogie et al.
18 citations as recorded by crossref.
- A Citizen Science Approach for Analyzing Social Media With Crowdsourcing C. Bono et al.
- Review article: Detection of actionable tweets in crisis events A. Kruspe et al.
- Towards a study of everyday geographic information: Bringing the everyday into view S. De Sabbata et al.
- Integrating social media data and machine learning methods for flash flood susceptibility mapping in China Y. Zhuang et al.
- A multimodal GeoAI approach to combining text with spatiotemporal features for enhanced relevance classification of social media posts in disaster response D. Hanny et al.
- R2D-EQ: a two-stage workflow for risk reasoning and decision-making in earthquake emergency scenarios L. Yao et al.
- AFAD Akreditasyon Sistemi’ne Başvuru Yapan Bir Kuruluşta Kentsel Arama Kurtarma Ekibi için Personel Seçimi T. Danışan & T. Eren
- What to do if there’s a nuclear attack? A quality and readability analysis of websites Y. Solak et al.
- Insurance as an Alternative for Sustainable Economic Recovery after Natural Disasters: A Systematic Literature Review . Kalfin et al.
- “Generalization of convolutional network to domain adaptation network for classification of disaster images on twitter” A. Khattar & S. Quadri
- Pathways to Socially Sustainable Adaptation: Real-Time and Context-Specific Vulnerability Assessment in South Carolina after Hurricane Dorian M. Batouli & D. Joshi
- HiDEF: A Hierarchical Disaster Information Extraction Framework Based on Adversarial Augmentation and Dynamic Prompting X. Wang et al.
- Quantifying socioeconomic impacts of urban pluvial flooding using social media and SDGSAT-1 nighttime light data: A case study of Kunming, China X. Zhang et al.
- The utility of using Volunteered Geographic Information (VGI) for evaluating pluvial flood models M. Drews et al.
- Environmental safety in the digital age: new methods and approaches E. Shchekotin
- The movement pattern changes of population following a disaster: Example of the Aegean Sea earthquake of October 2020 C. Varol et al.
- Shuiyuan DPT: a disaster management tool for a disaster resilient community M. Tsai et al.
- #RecoverSouthCoast: how Twitter can support and hinder recovery R. Ogie et al.
Saved (final revised paper)
Latest update: 04 May 2026
Short summary
In this paper, we study when social media is an adequate source to find metadata about incidents that cannot be acquired by traditional means. We identify six major use cases: impact assessment and verification of model predictions, narrative generation, recruiting citizen volunteers, supporting weakly institutionalized areas, narrowing surveillance areas, and reporting triggers for periodical surveillance.
In this paper, we study when social media is an adequate source to find metadata about incidents...
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