Disaster in the Headlines: Quantifying Narrative Variation in Global News Using Topic Modeling and Statistical Inference

Disaster in the Headlines: Quantifying Narrative Variation in Global News Using Topic Modeling and Statistical Inference

Understanding how disasters are framed in news media is critical to unpacking the socio-political dynamics of crisis communication. However, empirical research on narrative variation across disaster types and geographies remains limited. This study addresses that gap by examining whether media outle...

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Bibliographic Details
Main Authors: Fahim Sufi, Musleh Alsulami
Format: Article
Language:English
Published: MDPI AG 2025-06-01
Series:Mathematics
Subjects:
media bias
AI-driven crisis management
disaster narratives
topic modeling
crisis communication
open-source disaster data
Online Access:https://www.mdpi.com/2227-7390/13/13/2049
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https://www.mdpi.com/2227-7390/13/13/2049

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