From:
https://cs.stanford.edu/people/jure/talks/www08tutorial/, you need to
find datasets to implement these ideas. Check the above URLs for
DataSets (I did not check yet)
Part 4: Case studies
Communication
patterns of MSN Messenger. The application of above mentioned tools and
algorithms to a large network of communication on MSN Instant Messenger
(30 billion conversations, 240 million people).
Detecting
fraud on eBay. How to find fraudulent people on eBay. We present a
belief propagation method that is able to find fraudulent people in
large networks.
Monitoring
social and communication networks over time -- intrusion and outlier
detection. An application of tensor decomposition techniques to monitor
multiple time series over time and detect outliers and abnormal events
Web
projections. Exploiting the structure of web graph to predict the
quality of search results, user intention to reformulate queries and to
find spam search results.