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Twitter May Be Faster Than FEMA Models for Tracking Disaster Damage
by Rachel Nuwer
Real-time online activity could provide speedier assessments as disaster unfolds than tools currently used by the government agency
Social media is useful for more than just connecting with old high school friends and sharing cat videos. Twitter has become the go-to platform for breaking news on everything from the Boston Marathon bombing to the flyby of Pluto.
Now, research reveals that Twitter can also be used for rapid damage tracking after natural disasters—possibly even more quickly and expansively than similar assessments carried out by FEMA.
“It turns out the relationship between actual physical damage and the response online is quite strong,” says Yury Kryvasheyeu, a computational social scientist at Data61, an Australian digital and data innovation group. “You can get a quick, free signal that reliably maps the damage.”
This isn’t the first time Kryvasheyeu and his colleagues have used social media to gain real-world insights. They previously examined unemployment, epidemics and social mobilization through the lens of Twitter and other platforms. But this is the first time they’ve carried out an analysis on such an intensive timescale.
Rapid response in areas hardest hit by hurricanes, floods, earthquakes and other natural disasters can save lives and help first responders best allocate limited resources to places that are most in need. But traditional means used to identify high priority locales are surprisingly clumsy and expensive, often requiring personal visits to sites or aerial surveys.
As the researchers reported in Science Advances, combining the social media findings and the damage assessments on a map revealed significant overlap, with hardest hit areas also producing the most chatter on Twitter.
“For me, the biggest surprise was that this actually works so well, and that the signal is so strong,” Kryvasheyeu says.
Read the full story at Smithsonian.com here
- People, Places & Things/9-1-1magazine.com (via Smithsonian.com, 3/11/16)
Twitter image above found on the Internet, used as an example only.