Mapping the NFT revolution: market trends, trade networks, and visual features

Non Fungible Tokens (NFTs) are digital assets that represent objects like art, collectible, and in-game items. 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.

⚡ This is an original paraphrased summary — not copied from the abstract. Full paper available at the source link below.

• 1 They are traded online, often with cryptocurrency, and are generally encoded within smart contracts on a blockchain.
• 2 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.
• 3 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.

This research advances how AI systems learn, reason, and solve problems — with direct implications for automation and scientific discovery.

This summary is based on publicly available metadata and abstract. For the full research paper, visit the original source: