Real-Time Crisis Mapping Using Language Distribution

摘要

With the increase in GPS-enabled devices, social media sites, such as Twitter, are quickly becoming a prime outlet for timely geo-spatial data. Such data can be leveraged to aid in emergency response planning and recovery operations. Unfortunately, the information overload poses significant difficulty to the quick discovery and identification of emergency situation areas. The system tackles this challenge by providing real-time mapping of influence areas based on automatic analysis of the flow of discussion using language distributions. The workflow is then further enhanced through the addition of keyword surprise mapping which projects the general divergence map onto specific task-level keywords for precise and focused response.