Towards Web-Scale Observational Studies of Health - 2015

Explore a comprehensive lecture on leveraging social media analysis for public health surveillance and web-scale observational studies. Delve into the potential of social media to complement traditional health monitoring systems, tracking various conditions from influenza to mental health issues. Examine the framework for conducting large-scale observational studies, addressing challenges such as confounding and selection bias in social media analysis. Learn about innovative machine learning techniques for inferring latent user attributes, including demographics and location, using lightly supervised methods. Understand the importance of controlling for confounding factors in web-scale studies and their impact on research conclusions. Gain insights from Aron Culotta, an expert in text analysis and machine learning for public interest applications, as he shares his research and experiences in this cutting-edge field.