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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...

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Autores principales: Said, Anwar, Janjua, Muhammad Umar, Hassan, Saeed-Ul, Muzammal, Zeeshan, Saleem, Tania, Thaipisutikul, Tipajin, Tuarob, Suppawong, Nawaz, Raheel
Formato: Online Artículo Texto
Lenguaje:English
Publicado: PeerJ Inc. 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8670368/
https://www.ncbi.nlm.nih.gov/pubmed/34977356
http://dx.doi.org/10.7717/peerj-cs.815
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author Said, Anwar
Janjua, Muhammad Umar
Hassan, Saeed-Ul
Muzammal, Zeeshan
Saleem, Tania
Thaipisutikul, Tipajin
Tuarob, Suppawong
Nawaz, Raheel
author_facet Said, Anwar
Janjua, Muhammad Umar
Hassan, Saeed-Ul
Muzammal, Zeeshan
Saleem, Tania
Thaipisutikul, Tipajin
Tuarob, Suppawong
Nawaz, Raheel
author_sort Said, Anwar
collection PubMed
description 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.
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spelling pubmed-86703682021-12-30 Detailed analysis of Ethereum network on transaction behavior, community structure and link prediction Said, Anwar Janjua, Muhammad Umar Hassan, Saeed-Ul Muzammal, Zeeshan Saleem, Tania Thaipisutikul, Tipajin Tuarob, Suppawong Nawaz, Raheel PeerJ Comput Sci Data Mining and Machine Learning 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. PeerJ Inc. 2021-12-10 /pmc/articles/PMC8670368/ /pubmed/34977356 http://dx.doi.org/10.7717/peerj-cs.815 Text en ©2021 Said et al. https://creativecommons.org/licenses/by/4.0/This is an open access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, distribution, reproduction and adaptation in any medium and for any purpose provided that it is properly attributed. For attribution, the original author(s), title, publication source (PeerJ Computer Science) and either DOI or URL of the article must be cited.
spellingShingle Data Mining and Machine Learning
Said, Anwar
Janjua, Muhammad Umar
Hassan, Saeed-Ul
Muzammal, Zeeshan
Saleem, Tania
Thaipisutikul, Tipajin
Tuarob, Suppawong
Nawaz, Raheel
Detailed analysis of Ethereum network on transaction behavior, community structure and link prediction
title Detailed analysis of Ethereum network on transaction behavior, community structure and link prediction
title_full Detailed analysis of Ethereum network on transaction behavior, community structure and link prediction
title_fullStr Detailed analysis of Ethereum network on transaction behavior, community structure and link prediction
title_full_unstemmed Detailed analysis of Ethereum network on transaction behavior, community structure and link prediction
title_short Detailed analysis of Ethereum network on transaction behavior, community structure and link prediction
title_sort detailed analysis of ethereum network on transaction behavior, community structure and link prediction
topic Data Mining and Machine Learning
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8670368/
https://www.ncbi.nlm.nih.gov/pubmed/34977356
http://dx.doi.org/10.7717/peerj-cs.815
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