As emerging digital assets, NFTs are susceptible to anomalous trading behaviors due to the lack of stringent regulatory mechanisms, potentially causing economic losses. In this paper, we conduct the first systematic analysis of four non-fungible tokens (NFT) markets. Specifically, we analyze more than 25 million transactions within these markets, to explore the evolution of wash trade activities. Furthermore, we propose a heuristic algorithm that integrates the network characteristics of transactions with behavioral analysis, to detect wash trading activities in NFT markets. Our findings indicate that NFT markets with incentivized structures exhibit higher proportions of wash trading volume compared to those without incentives. Notably, the LooksRare and X2Y2 markets are detected with wash trading volume proportions as high as 94.5% and 84.2%, respectively.

翻译：作为新兴数字资产，NFT因缺乏严格的监管机制而易受异常交易行为的影响，可能造成经济损失。本文首次对四个非同质化代币（NFT）市场进行了系统性分析。具体而言，我们分析了这些市场中超过2500万笔交易，以探究虚假交易活动的演变规律。此外，我们提出了一种结合交易网络特征与行为分析的启发式算法，用于检测NFT市场中的虚假交易活动。研究结果表明，与无激励结构的NFT市场相比，具有激励机制的市场中虚假交易量占比更高。值得注意的是，LooksRare和X2Y2市场中检测到的虚假交易量占比分别高达94.5%和84.2%。