Aug 16, 9:30 PT: Mining Online Data Across Social Networks

Tuesday, August 16, 2011 | 9:30 am Pacific Time, 12:30 pm Eastern Time

The information we experience online comes to us continuously over time, assembled from many small pieces, and conveyed through our social networks. This merging of information, network structure, and flow over time requires new ways of reasoning about the large-scale behavior of information networks. Professor Jure Leskovec will discuss a set of approaches for tracking and predicting how information travels and mutates in online networks. Based on collecting more than 20 million blog posts and news media articles per day, he will discuss how to mine such data to capture and model temporal patterns in the news over a daily time-scale -- in particular, the succession of story lines that evolve and compete for attention. He will also discuss models to quantify the influence of individual media sites on the popularity of news stories and algorithms for inferring hidden networks of information flow.

The lecture will be broadcast online at no charge. If you would like to view the live broadcast, please register below so that we can send you the link prior to the event.

Presented By
This free, one-hour lecture is hosted online by the Stanford Center for Professional Development on Tuesday, August 16 at 9:30 am Pacific Time.

Jure Leskovec is an assistant professor of Computer Science at Stanford University where he is a member of the Info Lab and the Artificial Intelligence (AI) Lab. His research focuses on mining and modeling large social and information networks, their evolution, and diffusion of information and influence over them. Problems he investigates are motivated by large scale data, the Web, and on-line media. He has received six best paper awards, a ACM KDD dissertation award, the Microsoft Research Faculty Fellowship, and appeared on IEEE Intelligent Systems magazine's "AI's 10 to Watch".

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