COMP621U: Social Networks, Media and Transfer Learning
Spring 2011
Instructor: Qiang Yang
Tuesday/Thursday 15:00-16:20, Room 5583
Room changed to 2465 (Lift 25/26) after Feb 21,2011

Office Hour: Mondays 13:00-15:00

Course description:
This course surveys recent development in data mining and machine learning in the areas of social networks and social media, and transfer learning.  Posts can be found on the Twitter site, and course specific items are posted on the course newsgroup Course Newsgroup.

Course objective:
1. To introduce the concepts of data mining in social network analysis, social media and finally, transfer learning.
2. To help students gain knowledge in research in these areas.

Course outline/content (by major topics):
    1. Overview of Social Network Data Mining
    2. Overview of Social Media Data Mining
    3. Overview of Transfer Learning
    4. Selected readings in Social networks, social media and transfer learning

Reference books/materials: Online resources, conference and journal proceedings.

Grading scheme:
    - 10%: participation
    - 40%: presentation
    - 50%: proposal and completion report of course project (likely to be some part of ACM KDDCUP)

Course Outline


Social Networks and Graphs: Basic Concepts (PPT)

Feb 9 class: Comp 621U students are encouraged to attend the tutorials at ACM WSDM 2011 Conference, in Hong Kong, on Feb 9, 2011.

2 Community Detection and Graph-based Clustering
3 Information Influence, Diffusion and Outbreak Detection (Slides)

(Note: classroom changed to 2465 (Lift 25/26) after Feb 21,2011)

On Thursday, we will be discussing the following papers:

  1. J. Leskovec, A. Krause, C. Guestrin, C. Faloutsos, J. VanBriesen, N. Glance. Cost-effective Outbreak Detection in Networks. In Proc. KDD 2007 (Slides)
  2. M. Rodriguez, J. Leskovec, A. Krause, Inferring Networks of Diffusion and Influence. In Proc. KDD 2010 (Slides)
  3. Mislove et al. You are Who You Know WSDM 2010 (Slides)
  4. C. Tan, J. Tang, J. Sun, Q. Lin, F. Wang. Social action tracking via noise tolerant time-varying factor graphs. In Proc. of KDD 2010 (Slides)
  5. Pal and Counts, Identifying Topical Authorities in Microblogs, WSDM 2011 (PPT) ( also read the TwitterRank Paper, Slides)

Link Prediction and Collaborative Filtering (Slides)


5 Social Tagging and Learning

Other Readings

  • Collective intelligence and Crowd-sourcing
  • Transfer Learning in Social Network Applications
7-13 Student Presentations (March 22--May 12)


May 17 Final Project Due

Data Sets


Other References