Blockchain Network Analysis: A Comparative Study of Decentralized Banks

Zhang, Yufan; Chen, Zichao; Sun, Yutong; Liu, Yulin; Zhang, Luyao

doi:10.1007/978-3-031-37717-4_67

Cited by 8 publications

(3 citation statements)

References 29 publications

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“…1 DeFi offers a spectrum of on-chain services, including trading, borrowing, lending, and investing, all of which circumvent traditional intermediaries. [2][3][4][5][6][7][8] At the heart of this transformative ecosystem lie smart contracts, programmable software applications that facilitate the automation of financial transactions 9 . These smart contracts are deployed on blockchain networks, with Ethereum emerging as the dominant platform for DeFi activities.…”

Section: Background and Summarymentioning

confidence: 99%

“…Expanding the Dataset with Additional Network Attributes: While the current daily indices offer a robust foundation for empirical analysis within the DeFi ecosystem, it is evident that the breadth of our dataset can be broadened to include more comprehensive variables. These variables should encapsulate diverse facets of DeFi network systems, as referenced in existing literature, 31,33 including advanced network features, 4 intricate transaction fee mechanisms, 34,35 and the nuanced social sentiment dynamics [36][37][38] prevalent in DeFi networks. A particular area of interest for future investigations is the security dimension within these networks, as outlined in existing research.…”

Section: Future Research Directionsmentioning

confidence: 99%

“…Studies have indicated a tendency towards centralization within various layers of blockchain infrastructure and a somewhat myopic technological singularity perspective that often overlooks the critical aspect of decentralization in actual network utilization. 4,25,30,31 The concept of 'decentralization in usage' pertains to the quantitative assessment of user contributions to economic activities within blockchain networks and the distribution of these activities among network participants. Researchers utilizing our dataset are poised to conduct a nuanced exploration of the contrasts between Layer 1 (L1) and Layer 2 (L2) networks in terms of this decentralization metric.…”

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confidence: 99%

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Uniswap Daily Transaction Indices by Network

Chemaya,

Cong,

Joergensen

et al. 2023

Preprint

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Decentralized Finance (DeFi) is revolutionizing traditional financial services by enabling direct, intermediary-free transactions, thereby generating a substantial volume of open-source transaction data. This evolving DeFi landscape is particularly influenced by the emergence of Layer 2 (L2) solutions, which are poised to enhance network efficiency and scalability significantly, surpassing the existing capabilities of Layer 1 (L1) infrastructures. However, the detailed impact of these L2 solutions has been somewhat obscured due to a dearth of transaction data indices that can provide in-depth economic insights for empirical research. This study seeks to address this critical gap by conducting a comprehensive analysis of raw transactions sourced from Uniswap, a central decentralized exchange (DEX) within the DeFi ecosystem. The dataset encompasses an extensive collection of over 50 million transactions from both L1 and L2 networks. Additionally, we have curated a wide-ranging repository of daily indices derived from transaction trading data across prominent blockchain networks, including Ethereum, Optimism, Arbitrum, and Polygon. These indices shed light on crucial network dynamics, such as adoption trends, evaluations of scalability, decentralization metrics, wealth distribution patterns, and other key aspects of the DeFi landscape. This rich dataset serves as an invaluable tool, enabling researchers to dissect the complex interplay between DeFi and Layer 2 solutions, thus enhancing our collective understanding of this rapidly evolving ecosystem. Its notable contribution to the data science pipeline includes the implementation of a flexible, open-source Python framework, enabling the dynamic calculation of decentralization indices, customizable to specific research requirements. This adaptability makes the dataset particularly suitable for advanced machine learning applications, including deep learning, thereby solidifying its role as a critical asset in shaping Blockchain as the foundational infrastructure for the intelligent Web3 ecosystem.

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