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

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

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 pre...

Full description

Saved in:
Bibliographic Details
Published in:PeerJ. Computer science Vol. 7; p. e815
Main Authors: Said, Anwar, Janjua, Muhammad Umar, Hassan, Saeed-Ul, Muzammal, Zeeshan, Saleem, Tania, Thaipisutikul, Tipajin, Tuarob, Suppawong, Nawaz, Raheel
Format: Journal Article
Language:English
Published: United States PeerJ. Ltd 10-12-2021
PeerJ, Inc
PeerJ Inc
Subjects:
Algorithms
Analysis
Blockchain
Coders
Crypto-currencies
Data analysis
Data Mining and Machine Learning
Data Science
Digital currencies
Digital signatures
Distribution (Economics)
Emerging Technologies
Ethereum
Graph Neural Network
Graph neural networks
Graph representations
Network analysis
Network Community Structure
Power
Wealth
Wealth Distribution
Wealth Distribution
Network Community Structure
Ethereum
Graph Neural Network
Online Access:Get full text
Tags: Add Tag
No Tags, Be the first to tag this record!
Description
Summary: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.
Bibliography:ObjectType-Article-1
SourceType-Scholarly Journals-1
ObjectType-Feature-2
content type line 23
ISSN:2376-5992
2376-5992
DOI:10.7717/peerj-cs.815