AAAI Publications, Twenty-Ninth AAAI Conference on Artificial Intelligence

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Modeling Status Theory in Trust Prediction
Ying Wang, Xin Wang, Jiliang Tang, Wanli Zuo, Guoyong Cai

Last modified: 2015-02-18

Abstract


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.

Keywords


Trust Prediction, Status Theory, Matrix Factorization

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