Fitness preferential attachment as a driving mechanism in bitcoin transaction network

被引:15
作者
Aspembitova, Ayana [1 ,2 ]
Feng, Ling [2 ,3 ]
Melnikov, Valentin [4 ]
Chew, Lock Yue [1 ,4 ,5 ]
机构
[1] Nanyang Technol Univ, Div Phys & Appl Phys, 21 Nanyang Link, Singapore, Singapore
[2] Agcy Sci Technol & Res, Inst High Performance Comp, 1 Fusionopolis Way, Singapore, Singapore
[3] Natl Univ Singapore, Dept Phys, 2 Sci Dr 3, Singapore, Singapore
[4] Nanyang Technol Univ, Complex Inst, 50 Nanyang Ave, Singapore, Singapore
[5] Nanyang Technol Univ, Data Sci & Artificial Intelligence Res Ctr, Block N4 02a-32,Nanyang Ave, Singapore, Singapore
关键词
D O I
10.1371/journal.pone.0219346
中图分类号
O [数理科学和化学]; P [天文学、地球科学]; Q [生物科学]; N [自然科学总论];
学科分类号
07 ; 0710 ; 09 ;
摘要
Bitcoin is the earliest cryptocurrency and among the most successful ones to date. Recently, its dynamical evolution has attracted the attention of the research community due to its completeness and richness in historical records. In this paper, we focus on the detailed evolution of bitcoin trading with the aim of elucidating the mechanism that drives the formation of the bitcoin transaction network. Our empirical investigation reveals that although the temporal properties of the transaction network possesses scale-free degree distribution like many other networks, its formation mechanism is different from the commonly assumed models of degree preferential attachment or wealth preferential attachment. By defining the fitness value of each node as the ability of the node to attract new connections, we have instead uncovered that the observed scale-free degree distribution results from the intrinsic fitness of each node following a power-law distribution. Our finding thus suggests that the "good-get-richer" rather than the "rich-get-richer" paradigm operates within the bitcoin ecosystem. Based on these findings, we propose a model that captures the temporal generative process by means of a fitness preferential attachment and data-driven birth/death mechanism. Our proposed model is able to produce structural properties in good agreement with those obtained from the empirical bitcoin network.
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收藏
页数:20
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