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Research Fellows Directory

Jie Tang

Dr Jie Tang

Research Fellow


University of Southampton

Research summary

I work on data-mining and social-network analysis, with an emphasis on understanding the mechanism underlying the interaction between social and information networks. I plan to explore building models and algorithms for modeling the dynamics of social networks from the micro-level perspective. I have been working closely with data miners, sociologists, theorists, and social-network experts on real billion-scale social networks. My goal is to develop data-mining models and algorithms to help solve social-network modeling problems. My research has not only led to many publications in top data-mining, machine-learning, and web-search venues, but has also yielded real systems that have attracted millions of users from around the world.

More specifically, my research focuses on building models and algorithms for addressing challenging problems in heterogeneous information and social networks, including: 1) Information integration: acquire and integrate information (or knowledge) from multiple sources. 2) Social influence analysis: model and quantify topic-level social-influence factors in large social (or information) networks. 3) User behavior modeling: model and distinguish the effects of various social factors (e.g., influence, interest, and global trends) for predicting user behavior. Finally, based on the proposed technologies, we have developed two real systems:, which has attracted 6.32 million independent IP accesses from 220 countries/regions, and, which is one of the largest MOOC platforms in China.

Grants awarded

Discovering Object Patterns Arising from Heterogeneous, Evolutionary and Large-Scale Online Social Networks

Scheme: Newton Advanced Fellowship

Dates: Mar 2015 - Feb 2018

Value: £111,000