Trust and distrust prediction in social network with combined graphical and review-based attributes
KES-AMSTA'10 Proceedings of the 4th KES international conference on Agent and multi-agent systems: technologies and applications, Part I
Journal of Global Optimization
eTrust: understanding trust evolution in an online world
Proceedings of the 18th ACM SIGKDD international conference on Knowledge discovery and data mining
Exploiting homophily effect for trust prediction
Proceedings of the sixth ACM international conference on Web search and data mining
Knowledge-Based Systems
Trust-based authentication scheme with user rating for low-resource devices in smart environments
Personal and Ubiquitous Computing
Journal of Information Science
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Trust management is an increasingly important issue in large social networks, where the amount of data is too extensive to be analysed by ordinary users. Hence there is an urgent need for research aiming at building automated systems that can support users in making their decisions concerning trust.This work is a preliminary implementation of selected ideas described in our previous research proposal which concerns taking a machine-learning approach to the problem of trust prediction in social networks.We report experiments conducted on a publicly available social network dataset epinions.com. The results indicate that i) it is possible to predict trust to some extent, but much room for improvement is present; ii) enriching the model with attributes based on similarity between users can significantly improve trust prediction accuracy for more similar users.