Modeling Status Theory in Trust Prediction


  • Ying Wang Jilin University
  • Xin Wang Changchun Institute of Technology
  • Jiliang Tang Arizona State University
  • Wanli Zuo Jilin University
  • Guoyong Cai Guilin University of Electronic Technology



Trust Prediction, Status Theory, Matrix Factorization


With the pervasion of social media, trust has been playing more of an important role in helping online users collect reliable information. In reality, user-specified trust relations are often very sparse; hence, inferring unknown trust relations has attracted increasing attention in recent years. Social status is one of the most important concepts in trust, and status theory is developed to help us understand the important role of social status in the formation of trust relations. In this paper, we investigate how to exploit social status in trust prediction by modeling status theory. We first vertify status theory in trust relations, then provide a principled way to model it mathematically, and propose a novel framework sTrust which incorporates status theory for trust prediction. Experimental results on real-world datasets demonstrate the effectiveness of the proposed framework. Futher experiments are conducted to understand the importance of status theory in trust prediction.




How to Cite

Wang, Y., Wang, X., Tang, J., Zuo, W., & Cai, G. (2015). Modeling Status Theory in Trust Prediction. Proceedings of the AAAI Conference on Artificial Intelligence, 29(1).



Main Track: Machine Learning Applications