NFTVis: Visual Analysis of NFT Performance
Fan Yan Xumeng Wang Ketian Mao Wei Zhang Wei Chen
A non-fungible token (NFT) is a data unit stored on the blockchain. Nowadays,
more and more investors and collectors (NFT traders), who participate in
transactions of NFTs, have an urgent need to assess the performance of NFTs.
However, there are two challenges for NFT traders when analyzing the
performance of NFT. First, the current rarity models have flaws and are
sometimes not convincing. In addition, NFT performance is dependent on multiple
factors, such as images (high-dimensional data), history transactions
(network), and market evolution (time series). It is difficult to take
comprehensive consideration and analyze NFT performance efficiently. To address
these challenges, we propose NFTVis, a visual analysis system that facilitates
assessing individual NFT performance. A new NFT rarity model is proposed to
quantify NFTs with images. Four well-coordinated views are designed to
represent the various factors affecting the performance of the NFT. Finally, we
evaluate the usefulness and effectiveness of our system using two case studies
and user studies.