Twitter and other social media sites contain a wealth of information
about populations and has been used to track sentiment towards
products, measure political attitudes, and study social linguistics.
In this talk, we investigate the potential for Twitter and social
media to impact public health research. Broadly, we explore a range of
applications for which social media may hold relevant data, including
disease surveillance, public safety, and drug usage patterns. To
uncover these trends, we develop new statistical models that can
reveal trends and patterns of interest to public health from vast
quantities of data. Our results suggest that social media has broad
applicability for public health research.
Mark Dredze is an Assistant Research Professor in Computer Science at
Johns Hopkins University and a research scientist at the Human
Language Technology Center of Excellence. He is also affiliated with
the Center for Language and Speech Processing and the Center for
Population Health Information Technology. His research in natural
language processing and machine learning has focused on graphical
models, semi-supervised learning, information extraction, large-scale
learning, and speech processing. His recent work includes health
information applications, including information extraction from social
media, biomedical and clinical texts. He obtained his PhD from the
University of Pennsylvania in 2009.