  Non-fungible tokens (NFTs) as a decentralized proof of ownership represent
one of the main reasons why Ethereum is a disruptive technology. This paper
presents the first systematic study of the interactions occurring in a number
of NFT ecosystems. We illustrate how to retrieve transaction data available on
the blockchain and structure it as a graph-based model. Thanks to this
methodology, we are able to study for the first time the topological structure
of NFT networks and show that their properties (degree distribution and others)
are similar to those of interaction graphs in social networks. Time-dependent
analysis metrics, useful to characterize market influencers and interactions
between different wallets, are also introduced. Based on those, we identify
across a number of NFT networks the widespread presence of both investors
accumulating NFTs and individuals who make large profits.
