Social Network Analysis


Advances in Web 2.0 have led to increasing user participation in online social networks and changed the way users interact. This has attracted attracted considerable research in social network analysis with applications to viral marketing, online advertising, recommender systems, information diffusion, and experts finding.

In this project, we adopt a topology-based approach to analyze social networks for user recommendation and find influential users at a finer granularity over time. We are also interested to find brokers, or users who are strategically located in the network as gate-keepers to diffuse information across communities. We have developed a fast heuristic algorithm to find brokers based on the weak tie theory in sociology.

We also study the flow of both credible information and misinformation to design strategies to diminish the influence of misinformation. The results of our work can be used by local industry to understand the public knowledge of their products or services (as expressed in social media), whether this knowledge is credible or not, and how to better propagate favorable information through a network.

Selected Publications

  • Wee Yong Lim, Mong Li Lee, Wynne Hsu. iFact: An Interactive Framework to Assess Claims from Tweets, in International Conference on Information and Knowledge Management (CIKM), Singapore, November 2017.

  • Chonggang Song, Wynne Hsu, Mong Li Lee. Temporal Influence Blocking: Minimizing the Effect of Misinformation in Social Networks, in 33rd IEEE International Conference on Data Engineering (ICDE), San Diego, CA, USA, April 2017.

  • Chonggang Song, Wynne Hsu, Mong Li Lee. Targeted Influence Maximization in Social Networks, in 25th ACM International Conference on Information and Knowledge Management (CIKM), Indianapolis, United States, October 2016.

  • Wee Yong Lim, Mong Li Lee, Wynne Hsu. ClaimFinder: A Framework for Identifying Claims in Microblogs, in 6th International Workshop on Making Sense of Microposts (#Microposts), in conjunction with WWW Conference, Montreal, Canada, April 2016.

  • Chonggang Song, Wynne Hsu, Mong Li Lee. Mining Brokers in Dynamic Social Networks, in 24th ACM International Conference on Information and Knowledge Management (CIKM), Melbourne, Australia, October 2015.

  • Chonggang Song, Wynne Hsu, Mong Li Lee. Node Immunization over Infectious Period, in 24th ACM International Conference on Information and Knowledge Management (CIKM), Melbourne, Australia, October 2015.

  • Enliang Xu, Wynne Hsu, Mong Li Lee, Dhaval Patel. k-Consistent Influencers in Network Data, in 20th International Conference on Database Systems for Advanced Applications (DASFAA), Hanoi, Vietnam, April 2015.

  • Enliang Xu, Wynne Hsu, Mong Li Lee, Dhaval Patel. Inferring Topic-level Influence from Network Data, in 25th International Conference on Database and Expert Systems Applications (DEXA), Munich, Germany, September 2014.

  • Enliang Xu, Wynne Hsu, Mong Li Lee, Dhaval Patel. Incremental Mining of Top-k Maximal Influential Paths in Network Data, in Transactions on Large-Scale Data and Knowledge-Centered Systems (TLDKS), Vol 10, pp 173-199, 2013.

  • Gang Zhao, Mong Li Lee, Wynne Hsu. Community-based User Recommendation in Uni-directional Social Networks, in 22nd ACM International Conference on Information and Knowledge Management (CIKM), San Francisco, CA, USA, October 2013.

  • Wei Chen, Wynne Hsu, Mong Li Lee. Making Recommendations from Multiple Domains, in 19th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (SIGKDD), Chicago, Illinois, USA, August 2013.

  • Wei Chen, Wynne Hsu, Mong Li Lee. Modeling User's Receptiveness over Time for Recommendation, in 36th ACM SIGIR Conference, Dublin, Ireland, July 2013.

  • Enliang Xu, Wynne Hsu, Mong Li Lee, Dhaval Patel. Top-k Maximal Influential Paths in Network Data, in 23rd International Conference on Database and Expert Systems Applications (DEXA), Vienna, Austria, September 2012.

  • Gang Zhao, Mong Li Lee, Wynne Hsu, Jiawei Zhang. Query-based Personalized Search in Tag Social Systems, in 3rd Workshop on Social Web Search and Mining (SWSM), in conjunction with SIGIR Conference, Beijing, China, July 2011.