  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.
