Social Networks – Papers & People

Tracking the Growth of a Cascade (by Facebook about Facebook)

A Facebook research piece on cascades (subject matter is photos). The link: https://www.facebook.com/notes/facebook-data-science/can-cascades-be-predicted/10152056491448859

“In particular, we wanted to continuously track the growth of a cascade.

As certain photos become viral, and others die off, we are interested in tracking these photos in realtime, and understanding how well we can predict their future growth  as we continue to observe them.

For instance, if we have seen 5 reshares of a photo, what’s the probability that a further 5 reshares will happen? How does this compare with the case when we’ve seen 100 reshares, and want to know whether a further 100 reshares will happen?

More generally: if we have seen k reshares, what’s the probability that we will see another reshares?”

Research on Tumblr (by Yahoo!Labs about Tumblr)

By the folks at Yahoo!Labs: the authors “study the social network structure among Tumblr users, analyze its user-generated content, and describe reblogging patterns to analyze its user behavior.”, link here.

Some people (suggest more).

Lada Adamic at Facebook and at the University of Michigan School of Information and Center for the Study of Complex Systems. Her course at Coursera.

Albert-Laszlo Barabasi at Northeastern University, Department of Physics.

Matthew Jackson at Stanford’s Economics Department and his book and course at Coursera.

Jon Kleinberg at Cornell’s Computer Science Department and Department of Information Science.  His book with David Easley.

Jure Leskovec at Stanford University’s Department of Computer Science.

Duncan Watts at Microsoft Research, New York City.

 

 

 

 

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