FURI | Spring 2019

Developing a Model to Detect and Analyze the Presence of Important Emergency Care Factors via Twitter

Analyzing social media can offer insights into a wide range of topics that are commonly discussed online, providing valuable insights for tracking emergency care factors – medical conditions which may lead people to seek emergency care – across populations.  The goal of this research is to build an accurate model to analyze Twitter data to detect the presence of influenza outbreaks, serious trauma, and other medical conditions using Natural Language Processing techniques. The information gathered through this model can help emergency clinics to monitor these medical conditions in specific areas so that they can ensure proper preparation to deal with such phenomena.