|Title: Implicit User-Generated Content in the service of Public Health|
|Seminar: Computer Science|
|Speaker: Dr. Evgeniy Gabrilovich, Google Health|
|Contact: Eugene Agichtein, firstname.lastname@example.org|
|Date: 2021-10-29 at 1:00PM|
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Abstract: Every day millions of people use online products and services to satisfy their information needs. In the process of doing so, they produce large volumes of user-generated content (UGC). In this talk, we will distinguish between "explicit" UGC, which is intended to be made public (such as product ratings or reviews), and "implicit" UGC, which can be responsibly anonymized and aggregated in a privacy-preserving way to improve public health. We will analyze implicit UGC as a positive consumption externality, and will discuss its beneficial uses across a range of public health applications.
The bulk of this talk will focus on methods for aggregating and classifying the data to provide timely signals that help guide public health interventions and assess their efficacy. We will discuss applications such as estimating disease incidence, outbreak prediction, mitigating pandemic spread, and improving public health messaging.
Dr. Evgeniy Gabrilovich is a research director at Google Health where he leads the Public & Environmental Health team. Prior to joining Google in 2012, he was a director of research and head of the natural language processing and information retrieval group at Yahoo! Research. Evgeniy is an IEEE Fellow and ACM Distinguished Scientist. He is a recipient of the 2014 IJCAI-JAIR Best Paper Prize and the 2010 Karen Sparck Jones Award for his contributions to natural language processing and information retrieval. Evgeniy has served as a technical program chair for WSDM 2021, WWW 2017, and WSDM 2015. He earned his PhD in computer science from the Technion - Israel Institute of Technology. He also graduated (with extra credit) from the Executive MD training program at Harvard Medical School.
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