Utilizando Métricas de Centralidade para Analisar a Distribuição de Riqueza em Transações da Blockchain do Bitcoin
Resumo
Este estudo investiga a aplicação de quatro métricas de centralidade na rede complexa formada pelas transações de alto valor na blockchain do Bitcoin durante um período de 245 dias entre Junho de 2022 e Fevereiro de 2023, com o objetivo de identificar os nodos mais importantes para a distribuição de riqueza. Os resultados indicam que os endereços que mantêm sua centralidade e importância ao longo do tempo pertencem, principalmente, a grandes corretoras e entidades de custódia, que são descritas em detalhes no artigo. Além disso, o estudo revela que entre 91% e 94% dos endereços considerados centrais durante o período analisado não se repetem nos resultados. O estudo também mostra uma paridade nos principais resultados entre três métricas de centralidade utilizadas.
Referências
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Ho, K. H., Chiu, W. H., & Li, C. (2020). A Short-Term Cryptocurrency Price Movement Prediction Using Centrality Measures. In 2020 International Conference on Data Mining Workshops (ICDMW) (pp. 369-376). IEEE.
Pereira, D. M., & Couto, R. S. (2022). Using Degree Centrality to Identify Market Manipulation on Bitcoin. In Data Privacy Management, Cryptocurrencies and Blockchain Technology: ESORICS 2021 International Workshops, DPM 2021 and CBT 2021, Darmstadt, Germany, October 8, 2021, Revised Selected Papers (pp. 208-223). Cham: Springer International Publishing.
Tao, B., Dai, H. N., Wu, J., Ho, I. W. H., Zheng, Z., & Cheang, C. F. (2021). Complex network analysis of the bitcoin transaction network. IEEE Transactions on Circuits and Systems II: Express Briefs, 69(3), 1009-1013.
Kondor, D., Pósfai, M., Csabai, I., & Vattay, G. (2014). Do the rich get richer? An empirical analysis of the Bitcoin transaction network. PloS one, 9(2), e86197.
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Ebrahimi, M. S., & Babveyh, A. (2018). Predicting User Performance and Bitcoin Price Using Block Chain Transaction Network. arXiv preprint arXiv:1804.08044.
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Wuille, P. (2012). Hierarchical Deterministic Wallets. Bitcoin Improvement Proposal 32 (BIP0032). Bitcoin Github, November.
Palatinus, M., & Rusnak, P. (2014). Multi-account hierarchy for deterministic wallets. Bitcoin Improvement Proposal 44 (BIP0044). Bitcoin Github, April.
Hagberg, A., Swart, P., & S Chult, D. (2008). Exploring network structure, dynamics, and function using NetworkX (No. LA-UR-08-05495; LA-UR-08-5495). Los Alamos National Lab.(LANL), Los Alamos, NM (United States).
Remy, C., Rym, B., & Matthieu, L. (2018). Tracking bitcoin users activity using community detection on a network of weak signals. In Complex Networks & Their Applications VI: Proceedings of Complex Networks 2017 (The Sixth International Conference on Complex Networks and Their Applications) (pp. 166-177). Springer International Publishing.
Di Francesco Maesa, D., Marino, A., & Ricci, L. (2018). Data-driven analysis of bitcoin properties: exploiting the users graph. International Journal of Data Science and Analytics, 6, 63-80.
Peshov, H., Todorovska, A., Marojevikj, J., Spirovska, E., Rusevski, I., Angelovski, G., ... & Trajanov, D. (2023, January). Using Centrality Measures to Extract Knowledge from Cryptocurrencies’ Interdependencies Networks. In ICT Innovations 2022. Reshaping the Future Towards a New Normal: 14th International Conference, ICT Innovations 2022, Skopje, Macedonia, September 29–October 1, 2022, Proceedings (pp. 76-90). Cham: Springer Nature Switzerland.
Bastian, M., Heymann, S., & Jacomy, M. (2009). Gephi: an open source software for exploring and manipulating networks. In Proceedings of the international AAAI conference on web and social media (Vol. 3, No. 1, pp. 361-362).
Simoes, J. E., Ferreira, E., Menasche, D. S., & Campos, C. A. (2021). Blockchain privacy through merge avoidance and mixing services: a hardness and an impossibility result. ACM SIGMETRICS Performance Evaluation Review, 48(4), 8-11.
Ferrin, D. (2015). A preliminary field guide for bitcoin transaction patterns. In Proc. Texas Bitcoin Conf..
Silva, C., Ramos, B., Oliveira, S., & Piccoli, R. (2018). Caracterização da Rede Bitcoin: Uma Visão sobre a Evolução de Blocos, Transações, Endereços e Saldos de 2009 até 2017. In Anais do I Workshop em Blockchain: Teoria, Tecnologias e Aplicações. Porto Alegre: SBC.
Emery, J. A., & Latapy, M. (2021). Full Bitcoin blockchain data made easy. In Proceedings of the 2021 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining (pp. 240-243).
Silva, L. P. Q., de Araújo, A. P., Cota, D. O., Cota, G. O., & Antonio, A. D. A. (2021). Utilizando HMM para previsao de preço e estratégia de investimento em criptomoedas BitCoin. In Anais do IV Workshop em Blockchain: Teoria, Tecnologias e Aplicações (pp. 134-147). SBC.
Ho, K. H., Chiu, W. H., & Li, C. (2020). A Short-Term Cryptocurrency Price Movement Prediction Using Centrality Measures. In 2020 International Conference on Data Mining Workshops (ICDMW) (pp. 369-376). IEEE.
Pereira, D. M., & Couto, R. S. (2022). Using Degree Centrality to Identify Market Manipulation on Bitcoin. In Data Privacy Management, Cryptocurrencies and Blockchain Technology: ESORICS 2021 International Workshops, DPM 2021 and CBT 2021, Darmstadt, Germany, October 8, 2021, Revised Selected Papers (pp. 208-223). Cham: Springer International Publishing.
Tao, B., Dai, H. N., Wu, J., Ho, I. W. H., Zheng, Z., & Cheang, C. F. (2021). Complex network analysis of the bitcoin transaction network. IEEE Transactions on Circuits and Systems II: Express Briefs, 69(3), 1009-1013.
Kondor, D., Pósfai, M., Csabai, I., & Vattay, G. (2014). Do the rich get richer? An empirical analysis of the Bitcoin transaction network. PloS one, 9(2), e86197.
Albert, R., & Barabási, A. L. (2002). Statistical mechanics of complex networks. Reviews of modern physics, 74(1), 47.
Newman, M. E. (2003). The structure and function of complex networks. SIAM review, 45(2), 167-256.
Ebrahimi, M. S., & Babveyh, A. (2018). Predicting User Performance and Bitcoin Price Using Block Chain Transaction Network. arXiv preprint arXiv:1804.08044.
Chan, W. K., Chin, J. J., & Goh, V. T. (2020, December). Evolution of Bitcoin addresses from security perspectives. In 2020 15th International Conference for Internet Technology and Secured Transactions (ICITST) (pp. 1-6). IEEE.
Wuille, P. (2012). Hierarchical Deterministic Wallets. Bitcoin Improvement Proposal 32 (BIP0032). Bitcoin Github, November.
Palatinus, M., & Rusnak, P. (2014). Multi-account hierarchy for deterministic wallets. Bitcoin Improvement Proposal 44 (BIP0044). Bitcoin Github, April.
Hagberg, A., Swart, P., & S Chult, D. (2008). Exploring network structure, dynamics, and function using NetworkX (No. LA-UR-08-05495; LA-UR-08-5495). Los Alamos National Lab.(LANL), Los Alamos, NM (United States).
Remy, C., Rym, B., & Matthieu, L. (2018). Tracking bitcoin users activity using community detection on a network of weak signals. In Complex Networks & Their Applications VI: Proceedings of Complex Networks 2017 (The Sixth International Conference on Complex Networks and Their Applications) (pp. 166-177). Springer International Publishing.
Di Francesco Maesa, D., Marino, A., & Ricci, L. (2018). Data-driven analysis of bitcoin properties: exploiting the users graph. International Journal of Data Science and Analytics, 6, 63-80.
Peshov, H., Todorovska, A., Marojevikj, J., Spirovska, E., Rusevski, I., Angelovski, G., ... & Trajanov, D. (2023, January). Using Centrality Measures to Extract Knowledge from Cryptocurrencies’ Interdependencies Networks. In ICT Innovations 2022. Reshaping the Future Towards a New Normal: 14th International Conference, ICT Innovations 2022, Skopje, Macedonia, September 29–October 1, 2022, Proceedings (pp. 76-90). Cham: Springer Nature Switzerland.
Bastian, M., Heymann, S., & Jacomy, M. (2009). Gephi: an open source software for exploring and manipulating networks. In Proceedings of the international AAAI conference on web and social media (Vol. 3, No. 1, pp. 361-362).
Simoes, J. E., Ferreira, E., Menasche, D. S., & Campos, C. A. (2021). Blockchain privacy through merge avoidance and mixing services: a hardness and an impossibility result. ACM SIGMETRICS Performance Evaluation Review, 48(4), 8-11.
Ferrin, D. (2015). A preliminary field guide for bitcoin transaction patterns. In Proc. Texas Bitcoin Conf..
Publicado
22/05/2023
Como Citar
SCHEIBE, Guilherme A.; MARQUES-NETO, Humberto T..
Utilizando Métricas de Centralidade para Analisar a Distribuição de Riqueza em Transações da Blockchain do Bitcoin. In: WORKSHOP EM BLOCKCHAIN: TEORIA, TECNOLOGIAS E APLICAÇÕES (WBLOCKCHAIN), 6. , 2023, Brasília/DF.
Anais [...].
Porto Alegre: Sociedade Brasileira de Computação,
2023
.
p. 99-111.
DOI: https://doi.org/10.5753/wblockchain.2023.769.
