Categories
AI/ML Development
Data Visualization
Public Health
Tech Stack
Public Health Media Intelligence
In collaboration with the National Institutes of Health (NIH), we developed an AI/ML-powered software capable of identifying and mitigating misinformation on social media, including detecting bot-driven narratives, to strengthen public health response efforts.
Goal: Develop AI-driven digital tools to help public health organizations detect, track, and counter vaccine misinformation more efficiently, ultimately improving trust in vaccination programs and public health initiatives.
Problem:
40% of the U.S. population was hesitant to receive established and newly approved vaccines due to misinformation.
The spread of false narratives and coordinated bot activity undermined public trust, reducing vaccine adoption rates and jeopardizing public health efforts.
Public health agencies lacked scalable tools to monitor, detect, and counter misinformation effectively.
Solution:
Developed an AI/ML/NLP software that identifies COVID-19 vaccine misinformation with 70%+ accuracy (currently achieving ~80%).
Integrated bot detection capabilities to track and analyze misinformation campaigns.
Built a scalable framework to ingest, analyze, and respond to misinformation in real-time.
Leveraged AI/ML to support misinformation management, increasing efficiency and reducing response time.
Details:
Massive Data Processing: The system currently ingests:
2.5 billion COVID-19 vaccine-related tweets
250 million broadcast and podcast episodes
Operational Framework for Misinformation Management: AI/ML models are integrated into a structured response system, ensuring misinformation is identified and addressed swiftly.
Future-Ready Public Health Solutions: The AI-powered framework will be critical in future pandemic response efforts, enabling faster, data-driven decision-making for public health organizations.