GroupLens: an open architecture for collaborative filtering of netnews
CSCW '94 Proceedings of the 1994 ACM conference on Computer supported cooperative work
Social information filtering: algorithms for automating “word of mouth”
CHI '95 Proceedings of the SIGCHI Conference on Human Factors in Computing Systems
Communications of the ACM
Authoritative sources in a hyperlinked environment
Journal of the ACM (JACM)
Explaining collaborative filtering recommendations
CSCW '00 Proceedings of the 2000 ACM conference on Computer supported cooperative work
Mining the network value of customers
Proceedings of the seventh ACM SIGKDD international conference on Knowledge discovery and data mining
Methods and metrics for cold-start recommendations
SIGIR '02 Proceedings of the 25th annual international ACM SIGIR conference on Research and development in information retrieval
A logic for uncertain probabilities
International Journal of Uncertainty, Fuzziness and Knowledge-Based Systems
Evaluating collaborative filtering recommender systems
ACM Transactions on Information Systems (TOIS)
ACM Transactions on Information Systems (TOIS)
Propagation of trust and distrust
Proceedings of the 13th international conference on World Wide Web
Proceedings of the 10th international conference on Intelligent user interfaces
A trust-enhanced recommender system application: Moleskiing
Proceedings of the 2005 ACM symposium on Applied computing
IEEE Transactions on Knowledge and Data Engineering
Computing and applying trust in web-based social networks
Computing and applying trust in web-based social networks
Propagation Models for Trust and Distrust in Social Networks
Information Systems Frontiers
Identifying sets of key players in a social network
Computational & Mathematical Organization Theory
Improving collaborative filtering with trust-based metrics
Proceedings of the 2006 ACM symposium on Applied computing
Trust-enhanced visibility for personalized document recommendations
Proceedings of the 2006 ACM symposium on Applied computing
Naïve filterbots for robust cold-start recommendations
Proceedings of the 12th ACM SIGKDD international conference on Knowledge discovery and data mining
Enhanced Recommendations through Propagation of Trust and Distrust
WI-IATW '06 Proceedings of the 2006 IEEE/WIC/ACM international conference on Web Intelligence and Intelligent Agent Technology
A Trust-enabled P2P Recommender System
WETICE '06 Proceedings of the 15th IEEE International Workshops on Enabling Technologies: Infrastructure for Collaborative Enterprises
A new similarity measure for collaborative filtering to alleviate the new user cold-starting problem
Information Sciences: an International Journal
Whom should I trust?: the impact of key figures on cold start recommendations
Proceedings of the 2008 ACM symposium on Applied computing
Detecting critical nodes in sparse graphs
Computers and Operations Research
Trust based recommender system for the semantic web
IJCAI'07 Proceedings of the 20th international joint conference on Artifical intelligence
Generating predictive movie recommendations from trust in social networks
iTrust'06 Proceedings of the 4th international conference on Trust Management
Exploring different types of trust propagation
iTrust'06 Proceedings of the 4th international conference on Trust Management
Alleviating the sparsity problem of collaborative filtering using trust inferences
iTrust'05 Proceedings of the Third international conference on Trust Management
Categorizing user interests in recommender systems
KES'10 Proceedings of the 14th international conference on Knowledge-based and intelligent information and engineering systems: Part II
Information Sciences: an International Journal
Semantic inference of user's reputation and expertise to improve collaborative recommendations
Expert Systems with Applications: An International Journal
Social factors in group recommender systems
ACM Transactions on Intelligent Systems and Technology (TIST) - Special section on twitter and microblogging services, social recommender systems, and CAMRa2010: Movie recommendation in context
An effective recommendation method for cold start new users using trust and distrust networks
Information Sciences: an International Journal
Novel personal and group-based trust models in collaborative filtering for document recommendation
Information Sciences: an International Journal
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Collaborative filtering recommender systems are typically unable to generate adequate recommendations for newcomers. Empirical evidence suggests that the incorporation of a trust network among the users of a recommender system can significantly help to alleviate this problem. Hence, users are highly encouraged to connect to other users to expand the trust network, but choosing whom to connect to is often a difficult task. Given the impact this choice has on the delivered recommendations, it is critical to guide newcomers through this early stage connection process. In this paper, we identify several classes of key figures in the trust network, namely mavens, frequent raters and connectors. Furthermore, we introduce measures to assess the influence of these users on the amount and the quality of the recommendations delivered by a trust-enhanced collaborative filtering recommender system. Experiments on a dataset from Epinions.com support the claim that generated recommendations for new users are more beneficial if they connect to an identified key figure compared to a random user.