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

Research output: Contribution to journalArticlepeer-review

Abstract

In the face of rapid population growth, urbanisation, and accelerating climate change, rapid and accurate disaster detection has become critical to minimise human and material losses. In this context, geo-social media (referring to georeferenced social media posts) data have proven to be a sensible data source for tracing disaster-related conversations, especially during flood events. However, current research often neglects the relationship between information from social media posts and their corresponding geographical context. In this paper, we examine the emergence of disaster-related social media topics in relation to hydrological and socio-environmental features at the watershed level during the 2021 western European flood, while focusing on transboundary river basins. Building on an advanced machine-learning-based topic modelling approach, we show the emergence of flood-related geo-social media topics in both river-basin-specific and cross-basin contexts. Our analysis reveals distinct spatio-temporal dynamics in the public discourse, showing that timely topics describing heavy rainfall or flood damage were closely tied to immediate environmental conditions in upstream areas, while post-disaster topics about helping victims or volunteering were more prevalent in less affected areas located in both upstream and downstream areas. These findings highlight how social media responses to disasters differ spatially across watersheds and underscore the importance of integrating geo-social media analysis into disaster coordination efforts, opening new opportunities for transboundary collaborations and the coordination of emergency response along border-crossing rivers.
Original languageEnglish
Pages (from-to)2351-2369
Number of pages19
JournalNatural Hazards and Earth System Sciences
Volume25
Issue number7
DOIs
Publication statusPublished - 15 Jul 2025

Funding

This research has been supported by the Fonds De La Recherche Scientifique (FNRS; grant no. Chargé de Recherche 2020-23, Sébastien Dujardin). In addition, this project has received funding from the European Commission – European Union under HORIZON EUROPE (HORIZON Research and Innovation Actions), grant agreement no. 101093003 (HORIZON-CL4-2022-DATA-01-01). This research has been supported by the Fonds De La Recherche Scientifique (FNRS; grant no. Chargé de Recherche 2020-23, Sébastien Dujardin). In addition, this project has received funding from the European Commission - European Union under HORIZON EUROPE (HORIZON Research and Innovation Actions), grant agreement no. 101093003 (HORIZON-CL4-2022-DATA-01-01). We would like to warmly thank Xavier Fettweis and Sébastien Doutreloup from the Climate Lab at the Department of Geography, University of Liège, for providing customised precipitation data tailored to our study area. This work was funded by the Belgian Fonds de la Recherche Scientifique (FNRS) under Sébastien Dujardin's postdoctoral fellowship 2020-23 and was approved by the UNamur's Comité d'Ethique en Sciences Humaines (2020/05).

FundersFunder number
Fonds de la Recherche Scientifique
European Commission
European Union
HORIZON Research and Innovation ActionsHORIZON-CL4-2022-DATA-01-01, 101093003
Fonds De La Recherche Scientifique - FNRS2020-23, 2020/05

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

  1. SDG 9 - Industry, Innovation, and Infrastructure
    SDG 9 Industry, Innovation, and Infrastructure
  2. SDG 12 - Responsible Consumption and Production
    SDG 12 Responsible Consumption and Production
  3. SDG 13 - Climate Action
    SDG 13 Climate Action

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