I'm watching one of the 2 hours videos from the Stanford professor. He looks like a college freshman! No offense intended.
Do you have any resources on how to use these tools (especially the python library), and examples of implementation? I'm interested in learning more and using these tools on real data, but don't necessarily want to spend the time learning all of the theory behind it.
Yup he is young, he did a post doc for a year at Cornell [under Prof. Kleinberg] after his PhD, and directly became Asst. Prof at Stanford.
Well you can start with reading this book http://www.cs.cornell.edu/home/kleinber/networks-book/ for overview, regarding application of these techniques are considered you can look for papers at recent WWW, NIPS,ICML conferences. The most popular and well studied areas are Link Prediction and Community Detection. The SNAP library comes with some good example code. You can also have a look at Divisi project at MIT Media Lab if you are interested in reasoning/ analogy over the networks.
For real datasets, there are a lot of encyclopedic datasets such as Wikipedia / DBPedia /Semantic Web/ Music Brainz, as well as social ones such as Twitter follower network dataset. If you are in a university, you can even get full Web Graph from Yahoo [for research use alone].
Do you have any resources on how to use these tools (especially the python library), and examples of implementation? I'm interested in learning more and using these tools on real data, but don't necessarily want to spend the time learning all of the theory behind it.