Articles | Volume 3, issue 1
https://doi.org/10.5194/gc-3-129-2020
© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/gc-3-129-2020
© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Rapid collaborative knowledge building via Twitter after significant geohazard events
Université de Paris, Institut de physique du globe de Paris, CNRS, 75005 Paris, France
Maud Devès
Université de Paris, Institut de physique du globe de Paris, CNRS, 75005 Paris, France
Université de Paris, Institut Humanités Sciences Sociétés, Centre de Recherche Psychanalyse Médecine et Société, CNRS, Paris, France
Stephen P. Hicks
Department of Earth Science and Engineering, Imperial College London, London, UK
Jean-Paul Ampuero
Université Côte d'Azur, IRD, CNRS, Observatoire de la Côte d'Azur, Géoazur, France
Remy Bossu
European-Mediterranean Seismological Centre, CEA,
91297 Arpajon Cedex, France
CEA Centre DAM Ile de France, 91297 Arpajon, France
Lucile Bruhat
Laboratoire de Géologie, UMR 8538, Ecole normale supérieure, PSL University, CNRS, Paris, France
Daryono
Earthquake and Tsunami Mitigation Division, Indonesian Agency for Meteorology Climatology and Geophysics, Kemayoran,
DKI Jakarta 10610, Indonesia
Desianto F. Wibisono
independent researcher: Semarang, Central Java, Indonesia
Laure Fallou
European-Mediterranean Seismological Centre, CEA,
91297 Arpajon Cedex, France
Eric J. Fielding
Jet Propulsion Laboratory, California Institute of Technology, Pasadena, California, USA
Alice-Agnes Gabriel
Department of Earth and Environmental Sciences, Ludwig-Maximilians-Universität München, Munich, Germany
Jamie Gurney
independent researcher: United Kingdom Earthquake Bulletin, UK
Janine Krippner
Global Volcanism Program, National Museum of Natural History, Smithsonian Institution, Washington DC, USA
Anthony Lomax
ALomax Scientific, Mouans-Sartoux, France
Muh. Ma'rufin Sudibyo
Local Disaster Management Office (BPBD), Kebumen, Central Java, Indonesia
Astyka Pamumpuni
Institut Teknologi Bandung, Jawa Barat 40132, Indonesia
Jason R. Patton
Department of Geology, Humboldt State University, California, USA
Helen Robinson
Powerful Earth, UK
Mark Tingay
Australian School of Petroleum, University of Adelaide, Frome Street 5005, Adelaide, Australia
Sotiris Valkaniotis
Koronidos 9, 42131 Trikala, Greece
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This paper focuses on the issue of population information about natural hazards and disaster risk. It builds on the analysis of the unique seismo-volcanic crisis on the island of Mayotte, France, that started in May 2018 and lasted several years. We document the gradual response of the actors in charge of scientific monitoring and risk management. We then make recommendations for improving risk communication strategies in Mayotte and also in contexts where comparable geo-crises may happen.
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Subject: Geoscience engagement | Keyword: Co-creation and co-production
Development of forecast information for institutional decision-makers: landslides in India and cyclones in Mozambique
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Mirianna Budimir, Alison Sneddon, Issy Nelder, Sarah Brown, Amy Donovan, and Linda Speight
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This paper extracts key learning from two case studies (India and Mozambique), outlining solutions and approaches to challenges in developing forecast products. These lessons and solutions can be used by forecasters and practitioners to support the development of useful, appropriate, and co-designed forecast information for institutional decision-makers to support more effective early action in advance of disasters.
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It is an aspiration to infer flow conditions from bedform morphology (e.g. riverbed ripples) where sedimentary structures preserve the geological past or in inaccessible environments (e.g. Mars). This study was motivated by the idea of better designing an AI (artificial intelligence) algorithm to do this by using lessons from non-AI (i.e. human) abilities, investigated using a geoscience communication activity. A survey and an artificial neural network are used in a successful proof of concept.
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Short summary
Among social media platforms, Twitter is valued by scholars to disseminate scientific information. Using two 2018 geohazard events as examples, we show that collaborative open data sharing and discussion on Twitter promote very rapid building of knowledge. This breaks down the traditional
ivory towerof academia, making science accessible to nonacademics who can follow the discussion. It also presents the opportunity for a new type of scientific approach within global virtual teams.
Among social media platforms, Twitter is valued by scholars to disseminate scientific...
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