Research Network Mapping
Mapping the structure of blockchain and Web3 research through co-authorship analysis, keyword networks, and institutional collaboration patterns.
Abstract
This study maps the structure of blockchain and Web3 research by analyzing 1,000 highly-cited papers sourced from the OpenAlex academic database (2015–2025). We construct three complementary networks — co-authorship (3,810 authors, 18,554 collaboration links), keyword co-occurrence (219 terms, 491 co-occurrence links), and institutional collaboration (1,449 institutions, 7,478 inter-institutional links) — and apply label propagation community detection to identify research clusters. Our analysis reveals 556 distinct author communities spanning IoT security, sustainable supply chains, smart contracts, 6G communications, healthcare data privacy, and more. The resulting mapping highlights collaboration patterns, thematic convergence across disciplines, and opportunities for cross-community knowledge transfer within the Web3 ecosystem.
Interactive Network Graph
Drag to pan, scroll to zoom. Switch between Co-authorship, Keywords, and Institutions tabs. Use the degree filter to show more or fewer nodes.
Findings: Author Communities
Top 25 research communities by total citation count. Communities are detected via label propagation on the co-authorship network.
Satellite Communication Systems, Human–computer interaction, Network architecture
Blockchain, Cryptocurrency, Modular design
Confidentiality, Swarm behaviour
Blockchain, Internet of Things, Human–computer interaction
Blockchain, Scalability, Internet of Things
Blockchain, Digital Marketing and Social Media, FinTech
Scrap, Electric vehicle, Greenhouse gas
Cryptocurrency, Blockchain, Smart contract
Blockchain, Software, Business process
Scripting language, Workflow, Raw data
Accountability, Sustainable development, Productivity
Internet of Things, Blockchain, Black box
Visible light communication, Free-space optical communication, Network architecture
Blockchain, Smart contract, Internet of Things
Blockchain, Data sharing, Reinforcement learning
Internet of Things, Agriculture, Blockchain
Contact tracing, Digital health, Public health
Reputation, Human–computer interaction, Database transaction
Blockchain, Health care, Single point of failure
Blockchain, Encryption, Internet of Things
Blockchain, Internet of Things, Proof-of-work system
Constellation, Communications satellite, Satellite
Blockchain, Smart contract, Emerging technologies
Supply chain, Blockchain, Supply chain management
Climate change, Blockchain, Environmental resource management
Methodology
Data collection. Papers were sourced from OpenAlex, an open catalog of scholarly works. We queried for blockchain-related publications from 2015 onward and selected the top 1,000 by citation count to focus on high-impact work.
Network construction. Three networks were constructed: (1) a co-authorship network where two authors are linked when they co-author a paper, (2) a keyword co-occurrence network where keywords appearing together in the same paper are linked, and (3) an institutional collaboration network where two affiliations are linked when their researchers co-author.
Community detection. We applied label propagation, an iterative algorithm where each node adopts the most frequent label among its neighbors until convergence. This produces groups of densely connected authors who collaborate frequently — research communities.
Visualization. The interactive graph above uses D3.js force-directed layout. Node size reflects connection count; color indicates community membership. The degree filter adjusts the minimum number of connections required for a node to appear.
