Tutorial on Using Social Trust for Recommender Systems
Jennifer GolbeckACM RecSys’09, October 23–25, 2009, New York, New York, USA
ABSTRACT
As the Web has shifted to an interactive environment where vast amounts of content is created by users, the question of whom to trust and what information to trust has become both more important and more dicult to answer. At the same time, social networks have become very popular with
over a billion accounts shared across hundreds of networks. Social trust relationships, derived from social networks, are uniquely suited to speak to the quality of online information; recommender systems are designed to personalize, sort, aggregate, and highlight information. Merging social networks, trust, and recommender systems can improve the accuracy of recommendations and improve the user's experience. In this tutorial, we will cover the use of social trust in recommender systems. Topics including the computation of trust in social networks, integration of trust into recommender systems, and a discussion of when trust oers benets and
the challenges it presents.
Keywords: trust, social networks, recommender systems
1. TUTORIAL DESCRIPTION
these three learning objectives: -- Gain an introduction to social trust in online systems -- Receive an overview of major algorithms and techniques for computing with trust -- Learn about case studies where trust has been used for generating recommendations