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
GroupLens: applying collaborative filtering to Usenet news
Communications of the ACM
Analysis of recommendation algorithms for e-commerce
Proceedings of the 2nd ACM conference on Electronic commerce
Trust without touch: jumpstarting long-distance trust with initial social activities
Proceedings of the SIGCHI Conference on Human Factors in Computing Systems
Evaluating collaborative filtering recommender systems
ACM Transactions on Information Systems (TOIS)
Recommender Systems Research: A Connection-Centric Survey
Journal of Intelligent Information Systems
Proceedings of the 10th international conference on Intelligent user interfaces
Conversations in the Blogosphere: An Analysis "From the Bottom Up"
HICSS '05 Proceedings of the Proceedings of the 38th Annual Hawaii International Conference on System Sciences (HICSS'05) - Track 4 - Volume 04
A trust-enhanced recommender system application: Moleskiing
Proceedings of the 2005 ACM symposium on Applied computing
Data Mining: Concepts and Techniques
Data Mining: Concepts and Techniques
Investigating interactions of trust and interest similarity
Decision Support Systems
Trust-aware recommender systems
Proceedings of the 2007 ACM conference on Recommender systems
Trust and TAM in online shopping: an integrated model
MIS Quarterly
Generating predictive movie recommendations from trust in social networks
iTrust'06 Proceedings of the 4th international conference on Trust Management
Factors Affecting Bloggers' Knowledge Sharing: An Investigation Across Gender
Journal of Management Information Systems
Proceedings of the 12th International Conference on Electronic Commerce: Roadmap for the Future of Electronic Business
Factors Affecting Bloggers' Knowledge Sharing: An Investigation Across Gender
Journal of Management Information Systems
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Blogs give users a channel to express their knowledge and feelings with individuals worldwide, explaining the exponential growth of new blogs. However, due to the diverse subjects covered by bloggers, bloggers/readers have difficulty in finding valuable articles from the hundreds of millions of blogs on the Internet. To help ease information overload in the blogosphere, this work proposes a trust-enhanced collaborative filtering approach that integrates multi-faceted trust based on article type and user similarity. An online blog article recommender system, called iTrustU, is also designed to evaluate the effectiveness of the proposed approach in terms of accuracy and quality of recommendations. Results of a 45-day online experiment with 179 participants from the Internet demonstrate that the proposed integrated approach yields a significantly higher accuracy than traditional approaches, especially for cold-start users. Analysis results indicate that trust and similarity among bloggers/readers have a significantly positive correlation in the blogosphere. Effective recommender systems can be achieved by exploiting trust relationships in a trust network. The proposed approach is applicable not only to the blogosphere, but also to online social communities when trust relationships already exist between users.