Exploiting the `Web of Trust' to improve efficiency in collaborative networks

TL;DR

This paper proposes a trust-based framework for collaborative networks that enhances content quality assurance without manual review, using satisfaction scores derived from a web of trust, validated through simulations.

Contribution

It develops a novel trust-based mechanism to compute user satisfaction scores and analyzes the complexity of selecting reviewers, advancing quality control in collaborative systems.

Findings

Trust-based mechanisms improve review efficiency

The user selection optimization is NP-Hard

Simulations validate the effectiveness of the proposed model

Abstract

Maintaining high quality content is one of the foremost objectives of any web-based collaborative service that depends on a large number of users. In such systems, it is nearly impossible for automated scripts to judge semantics as it is to expect all editors to review the content. This catalyzes the need for trust-based mechanisms to ensure quality of an article immediately after an edit. In this paper, we build on previous work and develop a framework based on the `web of trust' concept to calculate satisfaction scores for all users without the need for perusing the article. We derive some bounds for systems based on our mechanism and show that the optimization problem of selecting the best users to review an article is NP-Hard. Extensive simulations validate our model and results, and show that trust-based mechanisms are essential to improve efficiency in any online collaborative editing platform.