The Mediatization of Internal Displacement: Do Media Reports Accurately Represent the Severity of Internal Displacement Driven by Flooding in Burundi as Captured by DTM?
On the 5th of June 2023, IOM’s Displacement Tracking Matrix (DTM) team in London hosted its first hackathon event in collaboration with UCL’s Institute for Risk and Disaster Reduction (IRDR). The event focused on team problem-solving and analysis to help tackle global questions on environmental and natural hazard related displacement. It encouraged student participants to utilise their GIS, quantitative methods and/or data visualisation skills to develop new ideas, as well as gain first-hand insight into how data is collected and used in emergency contexts, humanitarian crises, and responses.
As the winners of the hackathon, Jasmine Andean, and Melanie Larre, both pursuing a Global Humanitarian Studies undergraduate degree at UCL, had the opportunity to develop their hackathon idea further together with DTM London from August to September. Their research focused on a comparative analysis between media reports of floods and DTM’s Emergency Tracking Tool (ETT) data on internal displacement driven by flooding in Burundi in 2021. Their aim was to determine whether there were differences in the relationship between the severity of an event and the resulting internal displacement across affected locations.
Due to data gaps in publicly available flood, precipitation, and hydrometeorological data for Burundi, the team explored the possibility of using media reports of flooding events as a proxy for event severity data. By analysing media coverage of Burundi’s floods and comparing it with DTM’s ETT data, they observed that media attention on an event is contingent on a range of factors. These include the location of the flooding, death toll, geographic proximity and relevance to the media provider’s location of origin, ownership of the media platform, and local interest in a particular event or location. This demonstrated the unreliability of media reports as a source of data on disaster events, even though information from the media was often available earlier than official or operational data.
The team’s observations about ‘who counts’, both in the media and in current public disaster databases, raised questions about the representativeness of existing public data sources on flood events and their severity. Making data sources accessible is vital for building a knowledge base that will help actors better respond to disaster displacement.
Student Interview
To hear more about this student research project directly from the participants see the interview that was conducted on October 11.
Introduction
Student’s introduction to DTM and the data to be used on the hackathon.
Group work
Group work with DTM data on their selected topics.
Finalising outputs
Groups finalise their outputs and present them to IRDR and DTM .
Winner Selection
Winners, Melanie Larre and Jasmine Andean are invited to further develop their hackathon idea with DTM London.
Output
An output is created based on their work, in partnership with DTM, to encourage wider use of IOM's data amongst youth researchers.
Participating Students
Melanie Larre
Global Humanitarian Studies student at UCL, specialising in Data Science. Interested in the intersection between data science and the humanitarian sector, with previous experience with the Red Cross, E3G and volunteering with the Ramblers and the Starfish Greathearts foundation.
Media coverage in disaster events plays a crucial role in disseminating information to the public in a timely way and often precedes official data collection.
Jasmine Andean
Global Humanitarian Studies undergrad at UCL. She has a background in climate activism and is interested in displacement caused by environmental hazard, disaster and degradation, and law.
A lot of media sources are based in the global north and will not necessarily report on events occurring in Burundi; understanding the severity of a disaster would be challenging if media sources are regarded in isolation of official data.
Media can be useful, particularly in the aftermath of a disaster when official data collection is yet to commence, in these cases media can help us understand the initial responses to a disaster.