Under the Skin of Foundation NFT Auctions

TL;DR

This paper analyzes the Foundation NFT marketplace, uncovering underlying dynamics through social network analysis and developing a neural network model for NFT similarity, revealing auction performance patterns within clusters.

Contribution

It introduces a comprehensive analysis of Foundation NFTs, including social network insights and a neural network similarity model, providing new understanding of NFT auction behaviors.

Findings

NFT transfer network exhibits distinct structural properties

NFTs within the same cluster have similar auction performances

Neural network effectively clusters similar NFTs based on features

Abstract

Non Fungible Tokens (NFTs) have gained a solid foothold within the crypto community, and substantial amounts of money have been allocated to their trades. In this paper, we studied one of the most prominent marketplaces dedicated to NFT auctions and trades, Foundation. We analyzed the activities on Foundation and identified several intriguing underlying dynamics that occur on this platform. Moreover, We performed social network analysis on a graph that we had created based on transferred NFTs on Foundation, and then described the characteristics of this graph. Lastly, We built a neural network-based similarity model for retrieving and clustering similar NFTs. We also showed that for most NFTs, their performances in auctions were comparable with the auction performance of other NFTs in their cluster.