Real-time streaming intelligence: Integrating graph and NLP analytics

With the growth of social media, embedded sensors, and “smart” devices, those responsible for managing resources during emergencies, such as weather-related disasters, are transitioning from an era of data scarcity to data deluge. During a crisis situation, emergency managers must aggregate various data to assess the situation on the ground, evaluate response plans, give advice to state and local agencies, and inform the public. We make the case that social graph analysis and natural language modeling in real time are paramount to distilling useful intelligence from the large volumes of data available to crisis response personnel. Using ground truth information from social media data surrounding the 2012 Hurricane Sandy in New York City, we test and evaluate our real-time analytics platform to identify immediate and critical information that increases situational awareness during disastrous events.