Inferring binary trust relationships in Web-based social networks

Author:

Golbeck Jennifer1,Hendler James1

Affiliation:

1. University of Maryland, College Park, MD

Abstract

The growth of Web-based social networking and the properties of those networks have created great potential for producing intelligent software that integrates a user's social network and preferences. Our research looks particularly at assigning trust in Web-based social networks and investigates how trust information can be mined and integrated into applications. This article introduces a definition of trust suitable for use in Web-based social networks with a discussion of the properties that will influence its use in computation. We then present two algorithms for inferring trust relationships between individuals that are not directly connected in the network. Both algorithms are shown theoretically and through simulation to produce calculated trust values that are highly accurate.. We then present TrustMail, a prototype email client that uses variations on these algorithms to score email messages in the user's inbox based on the user's participation and ratings in a trust network.

Publisher

Association for Computing Machinery (ACM)

Subject

Computer Networks and Communications

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1. SentiTrust: A New Trust Model for Decentralized Online Social Media;IEEE Access;2023

2. Enhancing Trust Prediction in Attributed Social Networks with Self-Supervised Learning;Web Information Systems Engineering – WISE 2023;2023

3. BENCHMARKING THE INFLUENTIAL NODES IN COMPLEX NETWORKS;Advances in Complex Systems;2022-11

4. Attention-aware Multi-hop Trust Inference in Online Social Networks;2022 IEEE 9th International Conference on Data Science and Advanced Analytics (DSAA);2022-10-13

5. A Fuzzy System for Evaluating Trustworthiness of Users in a Social Network;IIUM Engineering Journal;2022-07-04

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