A Blockchain-Based Quality Control Model for Online Collaboration Systems

TL;DR

This paper proposes a blockchain-based model for quality control in online collaborative content generation, addressing security, privacy, and trust issues with a decentralized, transparent, and robust scoring system.

Contribution

It introduces a semi-iterative algorithm leveraging blockchain to compute artifact quality and node reputation, enhancing transparency and resistance to manipulation in academic informetrics.

Findings

Comparable performance to PageRank and HITS in quality scoring

Demonstrates robustness against malicious nodes

Shows efficiency in throughput and latency

Abstract

Collaborative content generation (CCG) enables collective creation of artifacts like scientific articles. Quality is a paramount concern in CCG, and a multitude of methods have been proposed to evaluate the quality of artifacts. Nevertheless, the majority of these methods are reliant on centralized architectures, which present challenges pertaining to security, privacy, and availability. Blockchain technology proffers a potential resolution to these challenges, by furnishing a decentralized and immutable ledger of quality scores. In this manuscript, we introduce a blockchain-based quality control model for CCG that uses a semi-iterative algorithm to interdependently compute quality scores of artifacts and reputation of nodes. Our model addresses critical challenges in academic informetrics, such as citation manipulation, transparency in collaborative scholarship, and decentralized trust in metric computation. Our model also exhibits sensitivity to processing latency, rendering it more agile in the presence of delays. Our model's quality scores, evaluated against PageRank and HITS baselines, show comparable performance, with additional assessments of throughput, latency, and robustness against malicious nodes confirming its reliability. A theoretical comparison with recent studies validates its feasibility for real world informetric application.