  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 their
market has experienced record sales, but little is known about the overall
structure and evolution of its 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 Ethereum and WAX blockchains. First, we characterize
statistical properties of the market. Second, we build the network of
interactions, show that traders typically specialize on NFTs associated with
similar objects and form tight clusters with other traders that exchange the
same kind of 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
stimulate further research on NFT production, adoption, and trading in
different contexts.
