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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. They are traded online, often with cryptocurrency, and are generally encoded within smart contracts on a blockchain. Public attention towards NFTs has exploded in 2021, when their market ha...
Autores principales: | , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Nature Publishing Group UK
2021
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8536724/ https://www.ncbi.nlm.nih.gov/pubmed/34686678 http://dx.doi.org/10.1038/s41598-021-00053-8 |
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author | Nadini, Matthieu Alessandretti, Laura Di Giacinto, Flavio Martino, Mauro Aiello, Luca Maria Baronchelli, Andrea |
author_facet | Nadini, Matthieu Alessandretti, Laura Di Giacinto, Flavio Martino, Mauro Aiello, Luca Maria Baronchelli, Andrea |
author_sort | Nadini, Matthieu |
collection | PubMed |
description | Non Fungible Tokens (NFTs) are digital assets that represent objects like art, collectible, and in-game items. They are traded online, often with cryptocurrency, and are generally encoded within smart contracts on a blockchain. 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. 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. First, we characterize statistical properties of the market. Second, we build the network of interactions, show that traders typically specialize on NFTs associated with similar objects and form tight clusters with other traders that exchange the same kind of objects. Third, we cluster objects associated to NFTs according to their visual features and show that collections contain visually homogeneous objects. 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. We anticipate that these findings will stimulate further research on NFT production, adoption, and trading in different contexts. |
format | Online Article Text |
id | pubmed-8536724 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | Nature Publishing Group UK |
record_format | MEDLINE/PubMed |
spelling | pubmed-85367242021-10-25 Mapping the NFT revolution: market trends, trade networks, and visual features Nadini, Matthieu Alessandretti, Laura Di Giacinto, Flavio Martino, Mauro Aiello, Luca Maria Baronchelli, Andrea Sci Rep Article Non Fungible Tokens (NFTs) are digital assets that represent objects like art, collectible, and in-game items. They are traded online, often with cryptocurrency, and are generally encoded within smart contracts on a blockchain. 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. 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. First, we characterize statistical properties of the market. Second, we build the network of interactions, show that traders typically specialize on NFTs associated with similar objects and form tight clusters with other traders that exchange the same kind of objects. Third, we cluster objects associated to NFTs according to their visual features and show that collections contain visually homogeneous objects. 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. We anticipate that these findings will stimulate further research on NFT production, adoption, and trading in different contexts. Nature Publishing Group UK 2021-10-22 /pmc/articles/PMC8536724/ /pubmed/34686678 http://dx.doi.org/10.1038/s41598-021-00053-8 Text en © The Author(s) 2021 https://creativecommons.org/licenses/by/4.0/Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . |
spellingShingle | Article Nadini, Matthieu Alessandretti, Laura Di Giacinto, Flavio Martino, Mauro Aiello, Luca Maria Baronchelli, Andrea Mapping the NFT revolution: market trends, trade networks, and visual features |
title | Mapping the NFT revolution: market trends, trade networks, and visual features |
title_full | Mapping the NFT revolution: market trends, trade networks, and visual features |
title_fullStr | Mapping the NFT revolution: market trends, trade networks, and visual features |
title_full_unstemmed | Mapping the NFT revolution: market trends, trade networks, and visual features |
title_short | Mapping the NFT revolution: market trends, trade networks, and visual features |
title_sort | mapping the nft revolution: market trends, trade networks, and visual features |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8536724/ https://www.ncbi.nlm.nih.gov/pubmed/34686678 http://dx.doi.org/10.1038/s41598-021-00053-8 |
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