Social Intelligence

Social intelligence for online social networks has attracted significant attention from researchers and practitioners. Social intelligence is the strategic use of social media data to address complex problems of social science by using and developing AI techniques, including deep learning, knowledge graph, agent-based modelling and natural language understanding.

Research areas

  • Social influence diffusion modelling and analysis
  • Influence maximisation algorithms
  • Undesirable influence minimisation
  • Misinformation/disinformation detection
  • Belief modelling with knowledge graphs and deep learning
  • Natural language understanding in the context of social networks
  • Information recommender systems
  • Machine learning methods include deep learning, transfer learning and reinforcement learning

Current projects

  • Responsible Artificial Intelligence
  • Misinformation/disinformation detection in online social networks
  • Social influence mining and analysis in complex networks
  • Aspect-based sentiment analysis with deep neural networks
  • Recommendation system with knowledge graphs
  • Image component recognition and reorganisation with deep neural networks

Research networks

  • A/Prof. Quan Bai, University of Tasmania, Australia
  • Prof. Jianhua Jiang, Jilin University of Finance and Economics, China
  • Prof. Liya Ding, Meiji University, Japan
  • Prof. Takayuki Ito, Kyoto University, Japan
  • Prof. Edmund Lai, Auckland University of Technology, New Zealand
  • Prof. William Wong, Auckland University of Technology, New Zealand
  • Prof. Verica Rupa, Auckland University of Technology, New Zealand
  • A/Prof. Xing Su, Beijing University of Technology, China
  • Dr Shiqing Wu, University of Technology Sydney, Australia
  • Dr Yi Yang, Hefei University of Technology, China


Theme leader

Student members

  • Jingli Shi (PhD)
  • Mengyan Wang (PhD)
  • Guan Wang (PhD)
  • Ruijun Li (MCIS)
  • Lexi Shi (MCIS)