Computer Science Colloquia
Monday, April 22, 2013
Host: Kamin Whitehouse
3:30 PM, Rice Hall Auditorium, followed by a light reception in Rice Hall Fourth Floor Atrium (west end)
Data Mining Massive Online Social Networks
Social interactions of hundreds of millions of people on the
Web create massive digital traces, which can naturally be represented,
studied and analyzed as massive networks of interactions. By
computationally analyzing such network data we can study phenomena that
were once essentially invisible to us: the social interactions and
collective behavior of hundreds of millions of people. In this talk we
discuss how computational perspectives and mathematical models can be
developed to abstract online social phenomena like: How will a community
or a social network evolve in the future? What are emerging ideas and
trends in the network? How does information flow and mutate as it is
passed from a node to node like an epidemic?
Bio: Jure Leskovec is assistant professor of Computer Science at Stanford University where he is a member of the Info Lab and the AI Lab. His research focuses on mining large social and information networks. Problems he investigates are motivated by large scale data, the Web and on-line media. This research has won several awards including best paper awards at KDD, WSDM, ICDM and ASCE Journal of Water Resources Planning and Management, ACM KDD dissertation award, Microsoft Research Faculty Fellowship, as well as Alfred P. Sloan Fellowship and Okawa Foundation Research grant. Jure received his bachelor's degree in computer science from University of Ljubljana, Slovenia, Ph.D. in machine learning from the Carnegie Mellon University and postdoctoral training at Cornell University. You can follow him on Twitter @jure.
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