Topic Models for Identifying Public Health Trends

22 Sep
Computer Science Colloquium Series
Mark Dredze, Johns Hopkins University
Thursday, September 22, 2016 -
4:00pm to 5:15pm
Maxwell Dworkin G115

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. To uncover these trends, we develop new topic models that can reveal trends and patterns of interest to public health from vast quantities of data.

Speaker Bio: 

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 focuses on public health informatics applications, including information extraction from social media, biomedical and clinical texts. He obtained his PhD from the University of Pennsylvania in 2009.

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