Title

To Trust or Not to Trust? Predicting Online Trusts Using Trust Antecedent Framework

Publication Type

Conference Proceeding Article

Publication Date

12-2009

Abstract

This paper analyzes the trustor and trustee factors that lead to inter-personal trust using a well studied Trust Antecedent framework in management science. To apply these factors to trust ranking problem in online rating systems, we derive features that correspond to each factor and develop different trust ranking models. The advantage of this approach is that features relevant to trust can be systematically derived so as to achieve good prediction accuracy. Through a series of experiments on real data from Epinions, we show that even a simple model using the derived features yields good accuracy and outperforms MoleTrust, a trust propagation based model. SVM classifiers using these features also show improvements.

Keywords

Trust prediction, trust ranking, trust antecedent framework

Discipline

Databases and Information Systems | Numerical Analysis and Scientific Computing

Research Areas

Data Management and Analytics

Publication

IEEE International Conference on Data Mining

First Page

896

Last Page

901

ISBN

9780769538952

Identifier

10.1109/ICDM.2009.115

Publisher

IEEE ICDM

City or Country

Miami, Florida, Dec 6-9

Additional URL

http://doi.ieeecomputersociety.org/10.1109/ICDM.2009.115