  NFTs (Non-Fungible Tokens) have seen significant growth since they first
captured public attention in 2021. However, the NFT market is plagued by fake
transactions and economic bubbles, e.g., NFT wash trading. Wash trading
typically refers to a transaction involving the same person or two colluding
individuals, and has become a major threat to the NFT ecosystem. Previous
studies only detect NFT wash trading from the financial aspect, while the
real-world wash trading cases are much more complicated (e.g., not aiming at
inflating the market value). There is still a lack of multi-dimension analysis
to better understand NFT wash trading. Therefore, we present the most
comprehensive study of NFT wash trading, analyzing 8,717,031 transfer events
and 3,830,141 sale events from 2,701,883 NFTs. We first optimize the dataset
collected via the OpenSea API. Next, we identify three types of NFT wash
trading and propose identification algorithms. Our experimental results reveal
824 transfer events and 5,330 sale events (accounting for a total of
\$8,857,070.41) and 370 address pairs related to NFT wash trading behaviors,
causing a minimum loss of \$3,965,247.13. Furthermore, we provide insights from
six aspects, i.e., marketplace design, profitability, NFT project design,
payment token, user behavior, and NFT ecosystem.
