Community Identification in Dynamic Heterogeneous Networks

Arizona State University, Computer Science and Engineering, Data Mining and Machine Learning


With social media, people can connect to each other more conveniently than ever. In some social networking sites, entities other than human beings can also be involved. For instance, in YouTube, a user can upload a video and another user can tag it. In other words, the users, videos, and tags are knit together in the same network. The ``actors'' in the network are not homogeneous.  Furthermore, examining activities of users, we can observe different interaction networks between the same set of actors.  Take YouTube as an example. A user can become a friend of another user; he can also subscribe to another user. The existence of different relations suggests that the interactions between actors are not homogeneous.  Networks involving heterogeneous actors or interactions are referred as heterogeneous networks. Accordingly,  heterogeneous networks can be categorized in two different types:
How to identify communities in dynamic heterogeneous networks is a challenging task.  Here, we  list some of our published works as well as the data sets collected from social media for evaluation purpose.


The dataset and script are freely available for academic and research use. The use of the dataset can be referenced to the following publication:
  author = {Lei Tang and Xufei Wang and Huan Liu}, 
  title = {Uncovering Groups via Heterogeneous Interaction Analysis}, 
  booktitle = {ICDM '09: Proceedings of IEEE International Conference on Data Mining},
  year = {2009}, 
  pages = {503-512}, 
The use of the dataset and code can be referenced to the following publication:
author = {Tang, Lei and Liu, Huan and Zhang, Jianping and Nazeri, Zohreh},
title = {Community evolution in dynamic multi-mode networks},
booktitle = {KDD '08: Proceeding of the 14th ACM SIGKDD international conference on Knowledge discovery and data mining},
year = {2008},
isbn = {978-1-60558-193-4},
pages = {677--685},
location = {Las Vegas, Nevada, USA},
doi = {},
publisher = {ACM},
address = {New York, NY, USA},





This project is sponsored by  MITRE (2008),  ONR-N000140810477 and AFOSR-FA95500810132.


Updated on 09/17/2009