The CDC and predictive analytics

The CDC had sophisticated models to estimate the spread of disease. However, they data they used was limited to quantitative data reported after-the-fact by doctors' offices, hospital emergency rooms, and urgent care centers.

The organization knew that in order to be truly predictive and thus more effective, they would need to incorporate real-time data from unstructured, text-based sources like Twitter.

Download the case study to get more information about how Luminoso:

  • Used text-based data to make their predictive analytics models more accurate and responsive

  • Detect and track key conversations happening on social media about the Ebola outbreak

  • Identify misinformation and conspiracy theories that needed to be refuted and corrected