In the dynamic landscape of the Web, we are witnessing the emergence of the Web3 paradigm, which dictates that platforms should rely on blockchain technology and cryptocurrencies to sustain themselves and their profitability. Cryptocurrencies are characterised by high market volatility and susceptibility to substantial crashes, issues that require temporal analysis methodologies able to tackle the high temporal resolution, heterogeneity and scale of blockchain data. While existing research attempts to analyse crash events, fundamental questions persist regarding the optimal time scale for analysis, differentiation between long-term and short-term trends, and the identification and characterisation of shock events within these decentralised systems. This paper addresses these issues by examining cryptocurrencies traded on the Ethereum blockchain, with a spotlight on the crash of the stablecoin TerraUSD and the currency LUNA designed to stabilise it. Utilising complex network analysis and a multi-layer temporal graph allows the study of the correlations between the layers representing the currencies and system evolution across diverse time scales. The investigation sheds light on the strong interconnections among stablecoins pre-crash and the significant post-crash transformations. We identify anomalous signals before, during, and after the collapse, emphasising their impact on graph structure metrics and user movement across layers. This paper pioneers temporal, cross-chain graph analysis to explore a cryptocurrency collapse. It emphasises the importance of temporal analysis for studies on web-derived data and how graph-based analysis can enhance traditional econometric results. Overall, this research carries implications beyond its field, for example for regulatory agencies aiming to safeguard users from shocks and monitor investment risks for citizens and clients.
The Web3 ecosystem runs on cryptocurrencies, which are prone to sudden, dramatic crashes. We study the 2022 collapse of the stablecoin TerraUSD and its companion token LUNA on the Ethereum blockchain using a multi-layer temporal graph, where each layer represents a different currency, letting us look at correlations between currencies and how the system evolved across different time scales. We find strong interconnections between stablecoins before the crash and major structural changes afterwards, and identify anomalous signals before, during and after the collapse. This is the first temporal, cross-chain graph analysis of a cryptocurrency collapse, and shows how graph-based methods can complement traditional econometric analysis for regulators and risk monitoring.
author = {Cheick Tidiane Ba and Ben Steer and Matteo Zignani and Richard G. Clegg},
title = {Investigating the Luna-Terra Collapse through the Temporal Multilayer Graph Structure of the Ethereum Stablecoin Ecosystem},
journal = {ACM Transactions on the Web},
year = {2025},
volume = {19},
number = {3},
doi = {10.1145/3726869}
}