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ORIGINAL RESEARCH article
Front. Commun.
Sec. Disaster Communications
Volume 10 - 2025 | doi: 10.3389/fcomm.2025.1553746
This article is part of the Research Topic Cross-Boundary Disaster Communication: Building Systems Thinking and Breaking Traditional Divisions in the Field View all 5 articles
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Floods are prevalent disasters in the United States (U.S.), with escalating risks due to climate change-induced factors like rising sea levels and erratic rainfall patterns. While organizational efforts to mitigate the social and economic impacts of floods exist, there is a continued need for innovative approaches to flood management, particularly in flood risk communication. Currently, flood risk communication remains largely one-directional (i.e., communication comes from organizational entities such as emergency services or the media and is not necessarily informed or updated by community need, which can limit preparedness and response capabilities). Prior studies have found that social media platforms offer valuable opportunities for more interactive and real-time dialogue during disasters, including flood events. Additionally, there is an established body of research exploring the communication relationships between communities and organizational entities, respectively; highlighting opportunities to better develop pathways for two-way communications. Our study builds upon this literature by examining the alignment between community and organizational messages on social media during a series of flooding events affecting nine U.S. states from July 2022 to August 2022. Specifically, the study uses Natural Language Processing (NLP) to compare the content, sentiment, and emotion of messages from each entity to assess whether official communications reflect public needs and effectively foster two-way communication. Results reveal key temporal and spatial trends in message frequency and topic focus across communities and organizational entities, from which we develop five targeted recommendations designed to support the execution of more effective two-way flood communication. Future work will provide further insights into tailoring communication strategies to more diverse populations and circumstances.
Keywords: flooding, natural language processing (NLP), Risk Communication, Social Media, Twitter/X
Received: 31 Dec 2024; Accepted: 03 Apr 2025.
Copyright: © 2025 Salley, Fox and Schubert. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
* Correspondence:
Christin Salley, University of Michigan, Ann Arbor, United States
Disclaimer: All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article or claim that may be made by its manufacturer is not guaranteed or endorsed by the publisher.
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