Class Meeting for 10-802 02/17/2011

This is one of the class meetings on the schedule for the course Social Media Analysis 10-802 in Spring 2011.

Overview

• Rest of the slides from 2-15.
• Slides for today's lecture.

Readings

• A survey of statistical network models, Goldenberg, Zheng, Fienberg, and Airoldi, Sections 1-3. (If you like, you can glance over Section 4.1 - 4.3, which give this author's view of some of the other models we've discussed.)
• I will also discuss some of the inference issues for estimating parameters of probabilistic graph models, and will discuss this short paper: Juuso Parkkinen, Adam Gyenge, Janne Sinkkonen and Samuel Kaski. A block model suitable for sparse graphs. In MLG 2009, The 7th International Workshop on Mining and Learning with Graphs, Leuven, Belgium, July 2-4,2009.

Optional Readings

I use these two papers as additional background:

• Snijders, T.A.B. & Nowicki, K., Estimation and prediction for stochastic block models for graphs with latent block structure. Journal of Classification, 14 (1997), 75 - 100.
• MS Handcock, AE Raftery, JM Tantrum, Model-based clustering for social networks, Journal of the Royal Stat Soc Series A, 2007, 170(2), pages 301-354

Some recent papers that could be presented at this point:

• Leskovec, J., D. Huttenlocher, and J. Kleinberg. 2010. Predicting positive and negative links in online social networks. In Proceedings of the 19th international conference on World wide web, 641–650.
• Leskovec, J., K. J Lang, and M. Mahoney. 2010. Empirical comparison of algorithms for network community detection. In Proceedings of the 19th international conference on World wide web, 631–640.