Social Network Mining@SMU
 
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Social Network Mining Research Group

 
Knowledge Discovery Systems Lab
80 Stamford Road, Singapore 178902  
Tel: +65-6828-0781       
Fax: +65-6828-0919
 
 
Group Calendar (access restricted to members only) 
 

Research

Our group focuses on mining structures and behaviors in social networks at various Web 2.0 sites, and applying the mine patterns in various search, annotation and recommendation applications.   

People

Faculty Members/Collaborators

Research Staff
PhD Students
* Please contact Ee-Peng Lim if you are interested to join us as researchers or students.

Prototype Systems

 
leniency aware rating system (http://ratings.smu.edu.sg)
 
This system addresses rating bias caused by raters. leniency (or strictness). Given a set of rating scores, their raters and rated objects, the system returns a quality score for each rated object derived from the rating scores on the object adjusted by the leniency (or strictness) of raters. Here, we define a more lenient rater to be one who gives higher ratings to the objects he/she rates compared with other co-raters of the objects. Conversely, a less lenient rater is one who gives lower ratings to the objects compared with other co-raters.
 

 

 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
semantic social network engine (http://www.cais.ntu.edu.sg/~ssnet/index.html)
 
 

Datasets 

Wikipedia Feature Article Nomination Dataset
This dataset is collected by Meiqun Hu and used for feature article nomination outcome prediction as reported in the paper below.  Please read the paper and download the dataset as long as due acknowledgement and reference to the following paper are made.
 
Meiqun Hu, Ee-Peng Lim, Ramayya Krishnan, Predicting Outcome for Collaborative Featured Article Nomination in Wikipedia, 3rd International AAAI Conference on Weblogs and Social Media (ICWSM2009), San Jose, May 2009.
 

Projects and Publications 

Rating Network Mining
(funded by A*Star, Singapore)
Trust Network Mining
(funded by National Research Foundation and A*Star, Singapore)
  • Jianshu Weng, Ee-Peng Lim, Jing Jiang, and Qi He, TwitterRank: Finding Topic-sensitive Influential Twitterers.  Third ACM International Conference on Web Search and Data Mining (WSDM 2010), New York City, February 2010.

    • Ee-Peng Lim, Viet-An Nguyen, Aixin Sun, Jing Jiang, and Hwee Hoon Tan, To Trust or Not to Trust? Predicting Online Trusts using Trust Antecedent Framework. IEEE International Conference on Data Mining (ICDM 2009), Miami, Florida, December 6-9, 2009
  • Nan Ma, Ee-Peng Lim, Viet-An Nguyen, Aixin Sun, Haifeng Liu, Trust Relationship Prediction Using Online Product Review Data. ACM CIKM Workshop on Complex Networks in Information and Knowledge Management (CNIKM2009), Hong Kong, November 2009.
  • Haifeng Liu, Ee-Peng Lim, Hady Wirawan Lauw, Minh-Tam Le, Aixin Sun, Jaideep Srivastava, Young-Ae Kim, Predicting Trusts among Users of Online Communities - An Epinions Case Study, ACM Conference on Electronic Commerce (EC2008), Chicago, July 2008.
  • Young-Ae Kim, Hady W. Lauw, Ee-Peng Lim, Jaideep Srivastava, Building a Web of Trust without Explicit Trust Ratings, ICDE Workshop on Data Engineering for Blogs, Social Media, and Web 2.0, in conjunction of 24th International Conference on Data Engineering, Cancun, Mexico, April 2008.  
Information Exchange Network Mining
(funded by Defense Science Organization, Singapore)
  • (in preparation)
 
Collaborative Authorship Network Mining
(funded by A*Star, Singapore)
Question Answer Network Mining
Miscellaneous
  • Hady Wirawan Lauw, Ee-Peng Lim, Web Social Mining, Encyclopedia of Library and Information Science, Taylor & Francis Group, 2009

 

Subpages (1): Mining Interaction Behaviors from Information Exchange Networks