Non Fungible Tokens (NFTs) are digital assets that represent objects like art, collectible, and in-game items. They are traded online, often with cryptocurrency, and are generally encoded within smart contracts on a blockchain. Public attention towards NFTs has exploded in 2021, when the NFT market has experienced record sales, but little is known about the overall structure and evolution of the NFT market. Here, we analyse data concerning 6.1 million trades of 4.7 million NFTs between June 23, 2017 and April 27, 2021, obtained primarily from the Ethereum and WAX blockchains. First, we characterize the statistical properties of the market. Second, we build the network of interactions and show that traders typically specialize on NFTs associated with similar objects. Third, we cluster objects associated to NFTs according to their visual features and show that collections contain visually homogeneous objects. Finally, we investigate the predictability of NFT sales using simple machine learning algorithms and find that sale history and, secondarily, visual features are good predictors for price. We anticipate that these findings will inform further research on NFT production, adoption, and trading in different contexts.

翻译：不可磨灭 Tokens (NFT) 是代表艺术、可采集和游戏中物品等物品的数字资产。 它们通常在网上交易, 通常使用加密货币进行交易, 并且通常在密链上的智能合同中进行编码。 2021年, 当NFT市场有创纪录的销售, 但对于NFT市场的整体结构和演变却知之甚少, 我们在此分析2017年6月23日至2021年4月27日主要从Etheum和WAX区块链获得的470万个NFT贸易的610万个数据。 首先, 我们描述市场的统计特性。 其次, 我们建立互动网络, 并显示交易商通常专门关注与类似物品相关的NFTs。 第三, 我们根据NFTs的视觉特征, 将与NFTs有关的物品集中起来, 显示收藏的有视觉等同的物品。 最后, 我们利用简单的机器学习算法来调查NFT销售的可预测性, 并发现销售历史和第二, 视觉特征是价格的好预测器。 我们预计这些结果将会为关于NFT的生产、 、 、 和不同环境的进一步研究。