Optimizing search engines using clickthrough data
Proceedings of the eighth ACM SIGKDD international conference on Knowledge discovery and data mining
The Eigentrust algorithm for reputation management in P2P networks
WWW '03 Proceedings of the 12th international conference on World Wide Web
Spreading Activation Models for Trust Propagation
EEE '04 Proceedings of the 2004 IEEE International Conference on e-Technology, e-Commerce and e-Service (EEE'04)
Computing and applying trust in web-based social networks
Computing and applying trust in web-based social networks
A web-based kernel function for measuring the similarity of short text snippets
Proceedings of the 15th international conference on World Wide Web
Personalized recommendation driven by information flow
SIGIR '06 Proceedings of the 29th annual international ACM SIGIR conference on Research and development in information retrieval
Attack-resistant trust metrics for public key certification
SSYM'98 Proceedings of the 7th conference on USENIX Security Symposium - Volume 7
Trust-aware recommender systems
Proceedings of the 2007 ACM conference on Recommender systems
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Recommender systems have been strongly researched within the last decade. With the arising and popularization of digital social networks a new field has been opened for social recommendations. Considering the network topology, users interactions, or estimating trust between users are some of the new strategies that recommender systems can take into account in order to adapt their techniques to these new scenarios. We introduce MarkovTrust, a way to infer trust from Twitter interactions and to compute trust between distant users. MarkovTrust is based on Markov chains, which makes it simple to be implemented and computationally efficient. We study the properties of this trust metric and study its application in a recommender system of tweets.