Research on Trust Prediction from a Sociological Perspective  

作　　者：王英 王鑫 左万利 

机构地区：[1]College of Computer Science and Technology, Jilin University, Changchun 130012, China [2]Key Laboratory of Symbolic Computation and Knowledge Engineering, Ministry of Education, Changchun 130012, China [3]School of Computer Technology and Engineering, Changehun Institute of Technology, Changchun 130012, China

出　　处：《Journal of Computer Science & Technology》2015年第4期843-858,共16页计算机科学技术学报（英文版）

基　　金：This work is supported by the National Natural Science Foundation of China under Grant No. 61300148, the Scientific and Technological Break-Through Program of Jilin Province of China under Grant No. 20130206051GX, and the Science and Technology Development Program of Jilin Province of China under Grant No. 20130522112JH.

摘　　要：Trust, as a major part of human interactions, plays an important role in helping users collect reliable infor-mation and make decisions. However, in reality, user-specified trust relations are often very sparse and follow a power law distribution; hence inferring unknown trust relations attracts increasing attention in recent years. Social theories are frameworks of empirical evidence used to study and interpret social phenomena from a sociological perspective, while social networks reflect the correlations of users in real world; hence, making the principle, rules, ideas and methods of social theories into the analysis of social networks brings new opportunities for trust prediction. In this paper, we investigate how to exploit homophily and social status in trust prediction by modeling social theories. We first give several methods to compute homophily coe？cient and status coe？cient, then provide a principled way to model trust prediction mathe-matically, and propose a novel framework, hsTrust, which incorporates homophily theory and status theory. Experimental results on real-world datasets demonstrate the effectiveness of the proposed framework. Further experiments are conducted to understand the importance of homophily theory and status theory in trust prediction.Trust, as a major part of human interactions, plays an important role in helping users collect reliable infor-mation and make decisions. However, in reality, user-specified trust relations are often very sparse and follow a power law distribution; hence inferring unknown trust relations attracts increasing attention in recent years. Social theories are frameworks of empirical evidence used to study and interpret social phenomena from a sociological perspective, while social networks reflect the correlations of users in real world; hence, making the principle, rules, ideas and methods of social theories into the analysis of social networks brings new opportunities for trust prediction. In this paper, we investigate how to exploit homophily and social status in trust prediction by modeling social theories. We first give several methods to compute homophily coe？cient and status coe？cient, then provide a principled way to model trust prediction mathe-matically, and propose a novel framework, hsTrust, which incorporates homophily theory and status theory. Experimental results on real-world datasets demonstrate the effectiveness of the proposed framework. Further experiments are conducted to understand the importance of homophily theory and status theory in trust prediction.

关 键 词：trust prediction homophily coefficient status coefficient social theory matrix factorization 

分 类 号：TP391.9[自动化与计算机技术—计算机应用技术] F270[自动化与计算机技术—计算机科学与技术]