Lecture Series

The Web Science Invited Lecture Series hosts distinguished guest speakers on a variety of topics related to web science. The lectures are free and open to the public. We are grateful to Yahoo! for their sponsorship during the 2008-2009 academic year.

Upcoming Lectures

Invited Web Science Lecture by Elizabeth Churchill, Yahoo!

Thursday, February 11, 2010 - 12:00pm — 1:00pm

Title and abstract to come!

Past Lectures

Felipe Ortega on "The Private Life of Wikipedia"

Friday, October 23, 2009 - 12:00pm — 1:30pm

Please come to a Web Science Lecture by Felipe Ortega!
The Private Life of Wikipedia

Centergy 335
(75 5th St.)

Abstract:
Despite the growing attention that scientific community has devoted to Wikipedia, available research works rarely focus beyond the English
version. Thus, there was a need for broader studies to understand the dynamics and evolution of the Wikipedia, as a whole. "Wikipedia: A quantitative analysis" is a PhD. dissertation that finally closes this gap. It provides an empirical, side-by-side analysis of the top 10

Web Science Talk with Cliff Lampe, "User Exit from Online Communities: A Case Study of Everything2"

Thursday, April 30, 2009 - 10:00am — 11:00pm

ABSTRACT
Everything2 is a user-generated encyclopedia started before Wikipedia,
but that has seen a declining membership since 2001. Started as a
spin-off of Slashdot, this site continues to generate quite a bit of
traffic, but has a hard time keeping new members, and old members
continue to leave for a variety of reasons. In this talk, I'll show
two examples of difficulty in socializing new members. First, I'll
show reactions to new users, and how those reactions have been
received. Second, I'll show an example of conflict between the site

Web Science Lecture by Malcolm Slaney, "We're drowning in Multimedia. Hurray!!!!"

Friday, March 13, 2009 - 11:00am — 12:00pm

"We're drowning in Multimedia. Hurray!!!!"
Malcolm Slaney
Yahoo! Research and Stanford CCRMA

Friday, March 13th, 11 am
TSRB 132

The wealth of data available on the Internet changes the way we think
about multimedia. Never before has there been so much multimedia data
available for training models and answering questions. But these new
riches bring with it a change in the problems we must think about. The
data is noisy and largely unlabeled --- we must make sense of it, often
returning an answer in hundreds of milliseconds. How do we understand


The Web Science Lecture Series is sponsored by a generous gift from