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Contribution Details

Type Conference or Workshop Paper
Scope Discipline-based scholarship
Published in Proceedings Yes
Title Personalised and Dynamic Trust in Social Networks
Organization Unit
Authors
  • Stefano Battiston
  • Frank E Walter
  • Frank Schweitzer
Presentation Type paper
Item Subtype Original Work
Refereed Yes
Status Published in final form
Language
  • English
ISBN 978-1-60558-435-5
Page Range 197 - 204
Event Title RecSys '09: Third ACM conference on Recommender systems
Event Type conference
Event Location New York
Event Start Date October 23 - 2009
Event End Date October 25 - 2009
Series Name Proceedings of the third ACM conference on recommender systems
Place of Publication New York
Publisher ACM Digital library
Abstract Text We propose a novel trust metric for social networks which is suitable for application to recommender systems. It is personalised and dynamic, and allows to compute the indirect trust between two agents which are not neighbours based on the direct trust between agents that are neighbours. In analogy to some personalised versions of PageRank, this metric makes use of the concept of feedback centrality and overcomes some of the limitations of other trust metrics. In particular, it does not neglect cycles and other patterns characterising social networks, as some other algorithms do. In order to apply the metric to recommender systems, we propose a way to make trust dynamic over time. We show by means of analytical approximations and computer simulations that the metric has the desired properties. Finally, we carry out an empirical validation on a dataset crawled from an Internet community and compare the performance of a recommender system using our metric to one using collaborative filtering.
Free access at DOI
Digital Object Identifier 10.1145/1639714.1639747
Other Identification Number merlin-id:10149
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