Social-Dimension Approach to Classification in Large-Scale Networks
Arizona State University, Computer Science and Engineering, Data Mining and Machine Learning
Social media often provides social network information of users.
However, the relationship hidden in the connections are
inhomogeneous. Social dimensions are introduced to represent the
heterogeneous interactions people interact with each other (latent
affiliations one actor is involved in). Here, we list some of our
published work as well as the data sets and code used for experiments.
Below are some of the data sets we have used for experiments in  and
. All are in matlab format. Each data set has two variables:
network and groups. "network" is a symmetric sparse matrix representing
the interaction between users, and "groups" are the groups subscribed
by users. We use that as the class labels in our work.
data of 10,312 nodes, 333, 983 links, and 39 categories.
- Flickr Data
of 80,513 nodes, 5, 899, 882 links, and 195 categories.
- YouTube Data
of 1, 138, 499 nodes, 2, 990, 443 links and 47 categories.
-  Lei Tang, Xufei Wang and Huan Liu. Scalable
Learning of Collective Behavior.
IEEE Transactions on Knowledge and Data Engineering (TKDE), To appear.
-  Lei Tang, and Huan Liu. Leveraging Social Media Networks for Classification. Journal of Data Mining and Knowledge Discovery (DMKD), 2011.
-  Lei Tang, Xufei Wang, Huan Liu and Lei Wang.
A Multi-Resolution Approach to Learning with Overlapping Communities
. In KDD Workshop on Social Media Analytics, 2010.
-  Lei Tang and Huan Liu.
Toward Predicting Collective Behavior via Social Dimension Extraction. In
IEEE Intelligent Systems,
-  Lei Tang and Huan Liu. Scalable
Learning of Collective Behavior
based on Sparse Social Dimensions. In Proceedings of the 18th
ACM Conference on Information and
Knowledge Management (CIKM’09),
-  Lei Tang and Huan Liu. Relational
Learning via Latent Social
Dimensions. In Proceedings of The 15th ACM SIGKDD Conference on
Knowledge Discovery and Data Mining (KDD’09), Pages 817–826,
-  Lei Tang. Collective
Behavior Prediction in Social Media. In
Doctoral Student Forum, SIAM International Conference on Data Mining
Other Related References
This project is sponsored by AFOSR-FA95500810132.
Updated on 7/29/2010