Articles | Volume 25, issue 7
https://doi.org/10.5194/nhess-25-2351-2025
https://doi.org/10.5194/nhess-25-2351-2025
Research article
 | 
15 Jul 2025
Research article |  | 15 Jul 2025

Tracing online flood conversations across borders: a watershed-level analysis of geo-social media topics during the 2021 European flood

Sébastien Dujardin, Dorian Arifi, Sebastian Schmidt, Catherine Linard, and Bernd Resch

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Cited articles

Aall, C., Holm, T. B., Cauchy, A., Rudolf, F., Harris, K., Jansen, M. K., Gobert, J., Lager, F., Arvis, B., and Bour, M.: Think global–act local: the challenge of producing actionable knowledge on transboundary climate risks at the sub-national level of governance, Frontiers in Climate, 5, 1170142, https://doi.org/10.3389/fclim.2023.1170142, 2023. 
Acikara, T., Xia, B., Yigitcanlar, T., Hon, C., Acikara, T., Xia, B., Yigitcanlar, T., and Hon, C.: Contribution of Social Media Analytics to Disaster Response Effectiveness: A Systematic Review of the Literature, Sustainability, 15, 8860, https://doi.org/10.3390/su15118860, 2023. 
BBC: In pictures: Floods kill dozens in Germany and Belgium, https://www.bbc.com/news/world-europe-57858826?utm (last access: 11 March 2025), 16 July 2021. 
Beigi, G., Hu, X., Maciejewski, R., and Liu, H.: An Overview of Sentiment Analysis in Social Media and Its Applications in Disaster Relief, in: Sentiment Analysis and Ontology Engineering, edited by: Pedrycz, W. and Chen, S., Studies in Computational Intelligence, Springer, Cham, 639, 313–340, https://doi.org/10.1007/978-3-319-30319-2_13, 2016. 
Blomeier, E., Schmidt, S., and Resch, B.: Drowning in the Information Flood: Machine-Learning-Based Relevance Classification of Flood-Related Tweets for Disaster Management, Information, 15, 149, https://doi.org/10.3390/info15030149, 2024. 
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Short summary
Our research explores how social media can help understand public responses to floods, focusing on the 2021 western European flood. We found that discussions varied by location and flood impact: in-disaster concerns were more common in severely affected upstream areas, while post-disaster topics dominated downstream. Findings show the potential of social media for improving disaster coordination along cross-border rivers in time-sensitive situations.
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