Information Diffusion on Twitter by @snikolov by Marti Hearst.
From the post:
Today Stan Nikolov, who just finished his masters at MIT in studying information diffusion networks, walked us through one particular theoretical model of information diffusion which tries to predict under what conditions an idea stops spreading based on a network’s structure (from the popular Easley and Kleinberg Network book). Stan also gathered a huge amount of Twitter data, processed it using Pig scripts, and graphed the results using Gephi. The video lecture below shows you some great visualizations of the spreading behavior of the data!
(video omitted)
The slides in his Lecture Notes let you see the Pig scripts in more detail.
Another deeply awesome lecture from Marti’s class on Twitter and big data.
Also an example of the level of analysis that a Twitter stream will need to withstand to avoid “imperial entanglements.”