A Blockchain-Based Quality Control Model for Online Collaboration Systems

2025-07-27

AI Summary

Centralized quality assessment methods for Collaborative Content Generation (CCG) in online collaborative systems suffer from privacy leakage, single-point failure, and lack of trust. Method: This paper proposes a blockchain-based decentralized quality evaluation framework featuring a novel semi-iterative cooperative algorithm that jointly computes content quality scores and node reputation values. The framework ensures transparency and trustworthiness via an immutable ledger and integrates throughput optimization, low-latency response, and robustness against malicious nodes. Contribution/Results: Experiments demonstrate that the proposed framework achieves content quality scoring accuracy comparable to PageRank and HITS, while significantly outperforming conventional approaches in throughput, response latency, and robustness. Theoretical analysis confirms its feasibility and scalability.

Technology Category

• Constraint Satisfaction and Optimization: Distributed CSP/Optimization
• Search and Optimization: Distributed Search
• Data Mining & Knowledge Management: Representing, Reasoning, and Using Provenance, Trust

Application Category

• Web Mining and Content Analysis: Web data quality in the era of algorithmically-generated content
• Economics, Online Markets and Human Computation: LLM based quality controls for crowd work
• Search and Retrieval-Augmented AI: Web evaluation methodologies and metrics

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.

Problem

• Decentralized quality control for collaborative content generation
• Addressing security and privacy in centralized quality evaluation
• Combating citation manipulation in academic informetrics

Innovation

• Blockchain-based decentralized quality control model
• Semi-iterative algorithm for interdependent scoring
• Latency-sensitive design for agile performance