Social Media Mining: Can We Prevent the Apocalypse?

During the 2013 Colorado flooding disaster, researchers from Penn State University used social media mining to track flooding hotspots. The researchers developed an algorithm to identify flooding hotspots based on photographs published by Twitter users during the disaster. There were over 150,000 “tweets” and over 22,000 photographs analyzed during the crisis in Colorado. This data ultimately aided responders in rescuing and evacuating more than 10,000 victims. This is a strong indicator that social media websites can be used to prevent, protect, and aid individuals during emergency situations. In December 2015, there were 1.59 billion active monthly users on Facebook and 307 million on Twitter. Due to the popularity of social media outlets, organizations such as the American Red Cross and the Federal Emergency Management Agency have begun tracking information published by users to gather information during disasters like the 2013 Colorado flooding. In response to the overwhelming benefits and use of social media sites, along with user self-reporting around the world, Digital Disease Detection (DDD) has emerged. DDD, also referred to as digital epidemiology, is a growing field in which scientists and computer analysts use algorithms to track the symptoms