A multidisciplinary group is looking to pair community leaders with machine learning, to help develop a tool capable of helping to respond to emergencies using social media. With initial work funded by a grant from the National Science Foundation, the team plans to take advantage of the expertise of community members to help train an artificial intelligence to disaster-related risks.
Says Chris Zobel, professor of business information technology in the Pamplin College of Business at Virginia Tech, of the need for the use of machine learning, “Because so many people use social media, there is a lot of data to dig through. Furthermore, because most people aren’t necessarily just tweeting about the crisis, you have to actively search through this data for the subset of information that is actually relevant.” It is this mass of data that is driving the use of community members, to help categorize tweets based on the type of information contained, so that the artificial intelligence can learn from these data sets how to best identify relevant information.
While starting with Twitter, the project is looking to eventually expand to other social media networks. “If we see a tweet with these particular characteristics, then most likely it is indicating that someone needs help,” says Zobel of the eventual goal. “This information can then be provided to emergency managers to give them a very focused view about what is actually happening and where, as the crisis evolves.”
Source:
https://vtnews.vt.edu/articles/2021/04/pamplin-zobel-cert.html
