May be of interest to some.

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Melody Clark
Communications Specialist
Technology & Social Change (TASCHA)
melcl...@uw.edu | 206.303.7910
Twitter: @taschagroup | @melodyrclark
tascha.uw.edu


 UW Data Science Seminar <http://data.uw.edu/seminar/> Analysis, Visualization 
& Discovery  Wednesday October 8, 3:30pm — 389 Mary Gates Hall  Can Cascades be 
Predicted?*Jure Leskovec* Assistant Professor of Computer Science, Stanford 
University

 Social networks play a central role in spreading of information, ideas, 
behaviors, and products. As such "contagions" diffuse from a person to person 
they may go "viral," and large cascades can form. However, a growing body of 
research has argued that virality and cascades may be inherently unpredictable. 
Thus, one of the central questions is whether information cascades can be 
predicted and possibly even engineered. In this talk, I will discuss a 
framework for predicting cascades and making them go viral.
We study large sample of cascades on Facebook and find strong performance in 
predicting whether a cascade will continue to grow in the future. The models we 
develop help us understand how to create viral social media
content: by using the right title, for the right community, at the right time.

BIO
Jure Leskovec <http://cs.stanford.edu/%7Ejure> is assistant professor of 
Computer Science at Stanford University. 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 a Microsoft Research Faculty Fellowship, the Alfred P. Sloan 
Fellowship and numerous best paper awards. Leskovec received his bachelor's 
degree in computer science from University of Ljubljana, Slovenia, and his PhD 
in in machine learning from the Carnegie Mellon University and postdoctoral 
training at Cornell University. You can follow him on Twitter @jure 
<http://www.twitter.com/jure>.


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Sarah A. Stone, PhD
Program Manager, eScience Institute
Computer Science and Engineering
Campus Box 352350
University of Washington
Seattle, WA 98195
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