Making Sense of Patterns in the Twitterverse
From the post:
If you think keeping up with what’s happening via Twitter, Facebook and other social media is like drinking from a fire hose, multiply that by 7 billion — and you’ll have a sense of what Court Corley wakes up to every morning.
Corley, a data scientist at the Department of Energy’s Pacific Northwest National Laboratory, has created a powerful digital system capable of analyzing billions of tweets and other social media messages in just seconds, in an effort to discover patterns and make sense of all the information. His social media analysis tool, dubbed “SALSA” (SociAL Sensor Analytics), combined with extensive know-how — and a fair degree of chutzpah — allows someone like Corley to try to grasp it all.
“The world is equipped with human sensors — more than 7 billion and counting. It’s by far the most extensive sensor network on the planet. What can we learn by paying attention?” Corley said.
Among the payoffs Corley envisions are emergency responders who receive crucial early information about natural disasters such as tornadoes; a tool that public health advocates can use to better protect people’s health; and information about social unrest that could help nations protect their citizens. But finding those jewels amidst the effluent of digital minutia is a challenge.
“The task we all face is separating out the trivia, the useless information we all are blasted with every day, from the really good stuff that helps us live better lives. There’s a lot of noise, but there’s some very valuable information too.”
The work by Corley and colleagues Chase Dowling, Stuart Rose and Taylor McKenzie was named best paper given at the IEEE conference on Intelligence and Security Informatics in Seattle this week.
Another one of those “name” issues as the IEEE conference site reports:
Courtney Corley, Chase Dowling, Stuart Rose and Taylor McKenzie. SociAL Sensor Analytics: Measuring Phenomenology at Scale.
I am assuming from the other researchers matching that this is the “Court/Courtney” in question.
I was unable to find an online copy of the paper but suspect it will eventually appear in an IEEE archive.
From the news report, very interesting and useful work.