Ethereum has revolutionized digital economies by enabling the creation of decentralized applications (DApps) powered by smart contracts. Central to these ecosystems are tokens—digital assets that represent value, ownership, or utility within blockchain networks. These tokens fall into two primary categories: fungible (ERC-20) and non-fungible (ERC-721). While both types facilitate economic activity on the Ethereum blockchain, their underlying mechanics, use cases, and network behaviors differ significantly.
This article presents a comprehensive comparison of ERC-20 and ERC-721 token transfer networks based on topological analysis. By modeling token transactions as graphs—where nodes represent users and edges represent transfers—we uncover key structural patterns, behavioral trends, and network dynamics that shape the Ethereum ecosystem.
Understanding Ethereum Tokens
Blockchain technology extends beyond cryptocurrency by enabling programmable digital assets through smart contracts. Ethereum, launched in 2015, introduced the Ethereum Virtual Machine (EVM), allowing developers to deploy self-executing code that governs asset creation, transfer, and ownership.
Tokens are among the most impactful innovations on Ethereum. They serve as transferable assets within DApps and can represent anything from digital art to financial instruments. The two dominant token standards are:
- ERC-20: Standard for fungible tokens—interchangeable units like currency.
- ERC-721: Standard for non-fungible tokens (NFTs)—unique digital assets with distinct properties.
Both standards define how tokens are created, transferred, and tracked via events logged on the blockchain. Specifically, every token transfer triggers a Transfer event recorded in transaction receipts, providing transparent, immutable data for analysis.
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Modeling Token Transfer Networks
To analyze economic behavior in Ethereum’s token ecosystems, researchers model transfer activity as network graphs. In this framework:
- Each node represents an Ethereum address (user or contract).
- Each edge represents at least one token transfer between two addresses.
This approach transforms raw blockchain data into structured networks, enabling the application of complex network theory to study connectivity, influence, and community formation.
Graph Construction Methodology
Using data from the first 15 million Ethereum blocks (July 2015 – June 2022), we extracted all Transfer events for ERC-20 and ERC-721 tokens. From these, we constructed transfer event graphs for the top 100 most active contracts by number of transfers.
Special care was taken to filter out minting events—transfers from null addresses used to create new NFTs—which could distort network topology. After cleaning, we analyzed key topological features including:
- Network size (nodes and edges)
- Density and clustering coefficient
- Diameter and average shortest path length
- Degree distribution and assortativity
These metrics help determine whether token networks exhibit characteristics like small-world structure, scale-free distribution, or centralized hub-and-spoke models.
Topological Differences Between ERC-20 and ERC-721 Networks
Despite originating from the same blockchain platform, fungible and non-fungible token networks display distinct structural traits.
Network Scale and Activity
ERC-20 networks are significantly larger:
- Average: 759,000 nodes and 1.7 million edges
- ERC-721 counterparts: ~21,000 nodes and 36,000 edges
This reflects the higher liquidity and transaction frequency of fungible tokens, often used in decentralized finance (DeFi) for trading, lending, and payments. In contrast, NFTs—representing collectibles, art, or in-game items—are traded less frequently due to their uniqueness.
Lack of Small-World Properties
Neither ERC-20 nor ERC-721 networks exhibit strong small-world characteristics, which combine short path lengths with high clustering (like social networks). Instead:
- Clustering coefficients are low (< 0.1), indicating weak community formation.
- Users tend to transact with "strangers" rather than within tight-knit groups.
This suggests that economic utility—not social trust—drives most token exchanges.
Degree Distribution and Scale-Free Behavior
Only 6% of ERC-20 networks follow a power-law degree distribution (scale-free), meaning most do not have a few dominant hubs. In contrast, 51% of ERC-721 networks show scale-free properties, indicating preferential attachment where popular NFTs attract more interactions.
Assortativity and Network Centralization
ERC-20 networks are more disassortative: high-degree nodes (e.g., exchanges) connect mostly with low-degree users. This reflects centralized trading patterns common in DeFi.
ERC-721 networks show milder disassortativity, suggesting more peer-to-peer transfers between collectors and creators—typical of decentralized marketplaces.
Path Lengths and Network Diameter
NFT networks have 1.6x longer relative path lengths than fungible token networks. This implies more extended chains of interaction, possibly reflecting multi-step resale processes or speculative trading loops.
Clustering Analysis: Do Application Domains Shape Network Structure?
A critical question is whether tokens serving similar purposes—such as gaming or digital art—develop comparable network topologies.
We categorized the top 100 contracts by application domain:
- ERC-20: 54% DeFi, 15% labeled "other"
- ERC-721: 48% PFPs (profile pictures), 18% gaming, 14% art
Clustering algorithms (K-means with PCA) were applied to group networks by topological similarity. Results showed:
- No clear correlation between application domain and network structure.
- Contracts in the same category often formed very different graphs.
- However, one notable exception emerged: spam-related NFT contracts consistently clustered together across all configurations.
These spam networks shared highly similar topologies—likely because spammers use a small set of addresses to distribute tokens widely, creating predictable star-like patterns.
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Temporal Evolution of Token Usage
Token popularity shifts over time, reflecting broader market trends.
ERC-20 Trends
- Pre-2018: Dominated by Layer-2 solutions.
- Post-2018: DeFi explosion—stablecoins and wrapped assets dominate transfers.
- By 2020: Top 3 contracts accounted for up to 80% of weekly transfers, showing strong concentration around trending platforms.
ERC-721 Trends
- Pre-2019: Limited activity; mainly gaming and virtual worlds.
- Late 2019: Surge due to Gods Unchained marketplace launch, responsible for nearly 98.5% of transfers in November alone.
- 2020–2021: Rise of PFPs (e.g., CryptoPunks, Bored Ape Yacht Club) and domain name services (ENS).
Both ecosystems show periodic concentration, where a few popular projects drive the majority of activity—a sign of trend-driven user behavior.
Frequently Asked Questions (FAQ)
What is the difference between ERC-20 and ERC-721 tokens?
ERC-20 tokens are fungible—each unit is identical and interchangeable, like dollars. They’re commonly used in DeFi for payments, staking, or governance. ERC-721 tokens are non-fungible—each is unique and represents ownership of a specific digital item, such as artwork or collectibles.
Why don’t token transfer networks form strong communities?
Unlike social networks, token transfers are driven by economic incentives rather than relationships. Users transact with exchanges or marketplaces they haven’t interacted with before, leading to low clustering and weak local communities.
Are NFT networks more decentralized than fungible token networks?
Generally yes. ERC-721 transfers occur more directly between users (peer-to-peer), while ERC-20 transactions often route through centralized hubs like exchanges—making NFT economies slightly more decentralized in structure.
How does spam affect NFT network topology?
Spam campaigns typically involve mass distribution from a few addresses to thousands of wallets. These create highly centralized, star-shaped networks with minimal secondary interaction—making them easily identifiable through graph analysis.
Can we predict which tokens will become popular?
While past performance isn’t guaranteed, trending tokens often emerge from strong communities, utility (e.g., access rights), or cultural relevance (e.g., celebrity endorsements). Network metrics like rising transfer volume and expanding user base can signal early adoption waves.
What future research directions are promising?
Future work could explore:
- Directed and weighted graphs incorporating transfer amounts or timestamps.
- Tracking individual NFTs across multiple owners using token IDs.
- Applying machine learning to detect anomalies or classify token types based on network structure.
Conclusion
The analysis of Ethereum’s ERC-20 and ERC-721 transfer networks reveals fundamental differences in scale, structure, and behavior. While both lack small-world properties and exhibit low density, fungible token networks are larger, more disassortative, and dominated by DeFi activity. Non-fungible token networks show greater decentralization but are heavily influenced by speculative trends and spam activities.
Importantly, there is no consistent link between a token’s purpose and its network topology—except in cases of spamming—highlighting the complexity of blockchain economies. As the ecosystem evolves, advanced graph-based analytics will remain essential for understanding user behavior, detecting fraud, and optimizing decentralized systems.
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