The Caribbean was shaken this week when Hurricane Dorian crept across the archipelago hammering infrastructure and battering both property and psyche of the unfortunate Bahamian people. While damage assessments are ongoing and will help estimate the scale of the economic damage and loss, there is also need to assess the scale of the mental trauma on residents. Existing technology has made such a feat not just possible but also provides opportunities for supporting those in need.
Although explicit details may not be available, with the use of technology we can still generate useful information that when acquired, or inferred, may help in estimating this often unappreciated damage and loss from hurricanes on the human psyche.
In the wake of a cybersecurity incident, investigators would typically inspect the logs and records produced during normal operation. The absence of records or logs can provide a useful indication of a system being offline, or misconfigured, or of sinister attempts to cover-up something. In other words, even a lack of data may be interpreted as a sign of data. How about that?
The passage of Hurricane Dorian provides a similar opportunity to detect the impact of the storm on those affected. A careful analysis of social media posts, both before and after the passage of the storm, may reveal that information. Amidst the casual posts of those commenting on the storm, inner details of feelings and emotions may be inferred by analysing the messages posted.
Interestingly, this technique does not only apply in the aftermath of tropical storms, but more generally for other forms of ecological grief, whether regarding the destruction of the Amazon rainforest, rapidly melting glaciers, or plastics in the environment.
This inference technique was the subject of a presentation made at the Sunbelt 2019 academic conference in Montreal earlier this year. In collaboration with some remarkable researchers, this technique was used to analyse ecological grief following the tropical storms of last year. The presentation on “How Machine Learning and Social Media Surveys Can Be Used to Assess Ecological Grief in Personal Networks of the Caribbean” was well received, but it holds promise for future application to improve our region’s resilience.
How well we react and adapt to our changing climate may ultimately define our ability to improve our resilience. If you look around and listen carefully, can you detect these signs?
Editor’s note:
Dr. Lyndell St Ville is an ICT Consultant with a background in environmental science. His expertise includes systems analysis, planning, and capacity building. To share your views, contact the author at: www.datashore.net or via The VOICE.