Framing of disaster impact in online news media: a case study from Malawi on flood risk management

Introduction: High-quality impact data is essential for several applications in disaster risk management including Early Warning Systems. Currently, most impact data have spatial and temporal gaps, especially in data-poor contexts. Local news media reporting on disasters can contain information to bridge these gaps. However, each news media outlet frames disasters differently, especially since disasters diffuse in time and space. This study addresses these challenges by interrogating the implications of varying depictions of disasters in media reporting and their added value for impact databases. Our case study focuses on Malawi for two reasons: first, it is a country prone to flooding and second, it is considered a data-poor country. Methods: Our dataset comprises of news articles from four quality leading national newspapers which were identified through a basic web search and an electronic database search of Malawian news outlets. We compare the impact information from these news articles with the disaster impact data from the international Emergency Events Database (EM-DAT). To comprehensively investigate our dataset, we applied natural language processing (NLP) techniques to break down and interpret news article texts and narratives, such as sentences and parts-of-speech. We worked with three linguistic annotations: part-of-speech tagging, named entity recognition, and sentiment analysis Results: The main conclusions from our analysis are that: (1) online news media has a human-focus framing – highlighting the role of crucial persons; and (2) online news media frame impact, such as economic consequences, at a granular level, which can help quantify flood damage. Discussion: We argue that our study has many valuable applications in other disaster-prone countries in the Majority World, given the high penetration of online news and social media Our study serves as a first step into better understanding the framing of disasters in online newspapers with social media presence to extract impact data and enrich institutional impact databases in a more insightful way. This study can help actors in disaster risk management focus on information from local news media to enrich existing impact data and to define triggers for disaster risk management.