CVCEJun 5, 2023

NFTVis: Visual Analysis of NFT Performance

arXiv:2306.02712v17 citationsh-index: 13
Originality Synthesis-oriented
AI Analysis

This addresses the need for NFT traders to analyze performance more effectively, though it appears incremental as it builds on existing visual analysis methods.

The paper tackles the problem of assessing NFT performance for traders by proposing NFTVis, a visual analysis system that includes a new rarity model and coordinated views, and evaluates it with case studies and user studies.

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.

Foundations

The foundational work for this paper's niche, ranked by how specifically the neighbourhood builds on it — not by global fame.

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