Key factors in social media information dissemination during disasters: A signaling theory perspective

Exploring the key factors affecting social media information dissemination during disasters can contribute to disaster management. On the basis of signaling theory, this study examines the impact of information source, location, amount, and appeal on public sentiment and information dissemination behaviors during disasters. It also analyzes how public sentiment influences information dissemination behaviors. By assessing a dataset of 2683 Weibo posts related to the 2023 Beijing flood, we found that all factors significantly influenced public sentiment and information dissemination behaviors, and official source increased reposts by 8.5%. Results support negativity bias theory, indicating that posts with negative sentiment attract considerable reposts. This study complements previous research on crisis communication by incorporating signaling theory into characteristic analysis from the perspectives of signal sender, signal, and signal receiver.

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Publication Details

Journal
Information Development
Published
2025-10-22
DOI
https://doi.org/10.1177/02666669251388124
Primary Topic
Misinformation and Its Impacts
Type
article
Field-Weighted Citation Impact
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article

Key factors in social media information dissemination during disasters: A signaling theory perspective

Huanhuan Jiang, Shanshan Zhang, Lingling Yu, Jun Li
Information Development
Misinformation and Its Impacts
article

Key factors in social media information dissemination during disasters: A signaling theory perspective

Huanhuan Jiang, Shanshan Zhang, Lingling Yu, Jun Li
article en

Abstract

Exploring the key factors affecting social media information dissemination during disasters can contribute to disaster management. On the basis of signaling theory, this study examines the impact of information source, location, amount, and appeal on public sentiment and information dissemination behaviors during disasters. It also analyzes how public sentiment influences information dissemination behaviors. By assessing a dataset of 2683 Weibo posts related to the 2023 Beijing flood, we found that all factors significantly influenced public sentiment and information dissemination behaviors, and official source increased reposts by 8.5%. Results support negativity bias theory, indicating that posts with negative sentiment attract considerable reposts. This study complements previous research on crisis communication by incorporating signaling theory into characteristic analysis from the perspectives of signal sender, signal, and signal receiver.

Information Development
Shanghai University (CN), Anhui University of Science and Technology (CN), Anhui Science and Technology University (CN), Zhejiang University of Technology (CN)
Openalex Percentile: Top 60%
Misinformation and Its Impacts
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