Dissecting Ethereum Blockchain Analytics: What We Learn from Topology and Geometry of the Ethereum Graph?

Abstract

Blockchain technology and, in particular, blockchain-based cryptocurrencies offer us information that has never been seen before in the financial world. In contrast to fiat currencies, all transactions of crypto-currencies and cryptotokens are permanently recorded on distributed ledgers and are publicly available. As a result, this allows us to construct a transaction graph and to assess not only its organization but to glean relationships between transaction graph properties and crypto price dynamics. The ultimate goal of this paper is to facilitate our understanding on horizons and limitations of what can be learned on cryptotokens from local topology and geometry of the Ethereum transaction network whose even global network properties remain scarcely explored. By introducing novel tools based on topological data analysis and functional data depth into Blockchain Data Analytics, we show that Ethereum network (one of the most popular blockchains for creating new crypto-tokens) can provide critical insights on price strikes of crypto-tokens that are otherwise largely inaccessible with conventional data sources and traditional analytic methods.

Detailed analysis of Ethereum network on transaction behavior, community structure and link prediction

“…Both Bitcoin and Ethereum are digital currencies; however, the fundamental aim of Ether (Ethereum transactional token) is to facilitate and monetize the operation of the smart contract and decentralized application platform, rather than establish itself as an alternative monetary system. While Bitcoin networks have been extensively investigated and analyzed in the previous literature, the recent emergence of Ethereum in 2015 has merely drawn attention from limited research, making it scarcely explored ( Li et al, 2020 ). Some of the recent studies that are relevant to the Ethereum data analysis is discussed here.…”

“…They have identified that top features associated with illicit activities include ‘Time diff between first and last(Mins)’, ‘Total Ether balance’, and ‘Min value received’. Li et al (2020) highlighted that all cryptocurrency and crypto-token transactions are permanently recorded on distributed ledgers and are publicly accessible, allowing for the development of a transaction graph and the analysis of connections between transaction graph characteristics and crypto price dynamics. They used the principles of persistent homology and functional data depth to study Ethereum crypto-tokens, particularly investigating price anomaly predictions and hidden co-movement between tokens.…”

“…However, most studies in this area still overlooked detailed analyses of the network community structures. While extensive studies have been performed on blockchain networks such as Bitcoin ( Nerurkar et al, 2021 ) due to its long establishment, network analyses on Ethereum are quite limited ( Li et al, 2020 ). Such analyses could play a crucial role in wealth distribution, the network’s relational structure, and the link predictability from heterogeneous network data.…”

Detecting Traffic Incidents Using Persistence Diagrams

“…Topological data analysis has been used previously in the context of traffic data: [19] uses TDA as a model for tracking vehicles and [20] uses TDA to understand individual travel behaviors. TDA has also been used previously for anomaly detection in [21,22]. TDA provides a framework for studying the "shape" of data in geometric and topological terms rather than a solely statistical framework [23][24][25].…”

“…TDA has been an extremely successful tool in applied algebraic topology across a multitude of applications, including analysis of neural networks [26,27], data dimension reduction techniques [28,29], anomaly detection [21,22] biological studies [30], viral evolution [31], the study of blood flow through brain arteries [32], and tracking vehicles [19]. TDA has been applied previously to study time-series data in a variety of settings [33,34].…”