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

Anwar Said; Muhammad Umar Janjua; Saeed-Ul Hassan; Zeeshan Muzammal; Tania Saleem; Tipajin Thaipisutikul; Suppawong Tuarob; Raheel Nawaz

doi:10.7717/peerj-cs.815

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

PeerJ Comput Sci. 2021 Dec 10:7:e815. doi: 10.7717/peerj-cs.815. eCollection 2021.

Authors

Anwar Said¹, Muhammad Umar Janjua¹, Saeed-Ul Hassan², Zeeshan Muzammal¹, Tania Saleem¹, Tipajin Thaipisutikul³, Suppawong Tuarob³, Raheel Nawaz⁴

Affiliations

¹ Department of Computer Science, Information Technology University, Lahore, Pakistan.
² Department of Computing and Mathematics, The Manchester Metropolitan University, Manchester, United Kingdom.
³ Faculty of Information and Communication Technology, Mahidol University, Salaya, Nakhon Pathom, Thailand.
⁴ Department of Operations, Technology, Events and Hospitality Management, Manchester Metropolitan University, Manchester, United Kingdom.

Abstract

Ethereum, the second-largest cryptocurrency after Bitcoin, has attracted wide attention in the last few years and accumulated significant transaction records. However, the underlying Ethereum network structure is still relatively unexplored. Also, very few attempts have been made to perform link predictability on the Ethereum transactions network. This paper presents a Detailed Analysis of the Ethereum Network on Transaction Behavior, Community Structure, and Link Prediction (DANET) framework to investigate various valuable aspects of the Ethereum network. Specifically, we explore the change in wealth distribution and accumulation on Ethereum Featured Transactional Network (EFTN) and further study its community structure. We further hunt for a suitable link predictability model on EFTN by employing state-of-the-art Variational Graph Auto-Encoders. The link prediction experimental results demonstrate the superiority of outstanding prediction accuracy on Ethereum networks. Moreover, the statistic usages of the Ethereum network are visualized and summarized through the experiments allowing us to formulate conjectures on the current use of this technology and future development.

Keywords: Ethereum; Graph Neural Network; Network Community Structure; Wealth Distribution.

Grants and funding

This research project is supported by Mahidol University, Thailand, and Blockchain Lab, ITU National Centre for Cyber Security (NCCS) Pakistan. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.