区块链游戏生态的角色动态识别与演化分析——以Axie Infinity为例

Dynamic Role Identification and Evolutionary Analysis of Blockchain Game Ecosystems:A Case Study of Axie Infinity

针对区块链游戏生态的复杂性,提出一种基于时序有向加权网络的新型角色识别方法。该方法首先设计了节点投票算法ChainVoteRank以识别出关键基础角色,然后结合多特征融合的层次聚类算法挖掘潜在的隐蔽角色。以play-to-earn(P2E)模式区块链游戏Axie Infinity为对象进行研究,结果表明该P2E模式区块链游戏生态中存在6种基本角色:劳工、正常玩家、经理、繁育商、交易商和机构组织。相较于传统角色识别方法,该方法不仅可以更好地识别出区块链游戏生态中的主要用户角色,而且还揭示了P2E模式区块链游戏生态的角色演化过程、不同阶段中各角色发挥的作用,以及P2E生态日益严重的贫富差距。

Given the intricate nature of blockchain game ecosystems,this study proposes a new role identification method based on a time-series directed weighted network.Specifically,this method first designs a new node voting algorithm called ChainVoteRank to identify key basic roles,and then uncovers potential hidden roles by combining hierarchical clustering algorithm with multi-feature fusion.Focusing on Axie Infinity,a“play-to-earn”(P2E)mode blockchain game,the research findings indicate that the existence of six fun-damental roles within the P2E mode blockchain game ecosystem:laborers,regular players,managers,breeders,traders,and institutional organizations.Compared with traditional methods,the proposed method can better identify the major user roles in the blockchain game ecosystem.Additionally,the study reveals the evolutionary process of roles within the P2E mode blockchain game ecosystem and the roles played by each role in different phases.Furthermore,a discussion of the escalating wealth disparity in P2E ecosystem is provided.