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www.nature.com/scientificreports/ Scientific Reports | Vol:.(1234567890) cleaned dataset includes 935 million USD traded in 6.1 million transactions involving 4.7 million NFTs grouped in 4624 collections. Our dataset includes transactions in 160 different cryptocurrencies with most of them made in WAX (52% of the total number of transactions), while the volume in USD is mostly ETH (81% of the total volume). We show general statistics of the categories of NFTs considered, involving a total of 359,561 buyers, 314,439 sellers, trading 4.7 millions NFTs involving 953 million USD in cryptocurrencies (see “SI”). Image collection and visual feature extraction. For each NFT in our dataset (except for less than 3000 exceptions) we managed to collect at least one URL that points to a copy of the NFT’s digital object. We focused only on objects with image file formats (e.g. PNG, SVG, JPEG) and GIFs, for a total of about 1.2 million unique graphical objects associated with 4.7 million unique NFTs. Note that a single digital object can be related to multiple NFTs; this happens for example for identical playing cards that are minted in multiple copies, each asso- ciated with a different NFT. Since our algorithm for visual feature extraction works with static images, we con- verted the animated GIFs to PNGs by extracting central frame of each GIF. In order to succinctly represent the visual features that characterize an image, we encode it into a latent space using a neural network. Specifically, we pick the PyTorch45 implementation of AlexNet46, a deep convolutional neural network architecture designed for image classification. We initialize AlexNet with weights pre-trained on ImageNet47, a widely-used reference dataset of labeled images. Given an image in input, AlexNet passes it through multiple layers of transformation. The second to last layer (i.e., the layer before the classification layer) is a vector consisting of 4096 values that constitute a dense representation of the input image into a high-dimensional space. These vectors can be used for a variety of tasks such as similarity ranking, clustering, or classification. To reduce the dimensionality of AlexNet vectors, we extracted their principal components using Principal Component Analysis (PCA)48, and selected the five most relevant ones. PCA projects each point of the high-dimensional space into a space with a desired number of dimensions, while preserving the data variation as much as possible. Data availability Data and scripts used to download from the different APIs are available at https://osf.io/wsnzr/?view_only= 319a53cf1bf542bbbe538aba37916537. Received: 19 July 2021; Accepted: 29 September 2021 References 1. Ben Luke, A. S. & Stoilas, H. WTF are NFTs? Why crypto is dominating the Art market. (2021). https://www.theartnewspaper. com/podcast/wtf-nfts. (Accessed 4 May 2021). (The Art Newspaper). 2. Team,N.Non-fungibletokensquarterlyreportQ12021.(2021).https://nonfungible.com/subscribe/nft-report-q1-2021.(Accessed 4 May 2021). (NonFungible Corporation). 3. Evans,T.M.Cryptokitties,cryptography,andcopyright.AIPLAQJ47,219–247(2019). 4. Lounge, T. W. Choosing the right blockchain for your NFT. (2020). https://medium.com/phantasticphantasma/choosing-the- right-blockchain-for-your-nft-d1df2bebae91. (Accessed 4 May 2021). (Medium). 5. Team, C. (2021). CryptoKitties: Collect and breed furrever friends. https://www.cryptokitties.co/. (Accessed 4 May 2021). (Cryptokitties). 6. Wong,J.I.TheEthereumnetworkisgettingjammedupbecausepeoplearerushingtobuycartooncatsonitsblockchain.(2017). https://qz.com/1145833/cryptokitties-is-causing-ethereum-network-congestion/. (Accessed 4 May 2021). (Quartz). 7. Tepper,F.Peoplehavespentover\$1mbuyingvirtualcatsontheEthereumblockchain.(2017).https://techcrunch.com/2017/12/ 03/people-have-spent-over-1m-buying-virtual-cats-on-the-ethereum-blockchain/. (Accessed 4 May 2021). (TechCrunch). 8. Riegelhaupt, R. Results: Beeple’s purely digital NFT-based work of Art achieves \$69.3 million at Christie’s. (2021). https://www. christies.com/about-us/press-archive/details?PressReleaseID=9970&lid=1. (Accessed 4 May 2021). (Christie’s Press Release). 9. Reyburn,S.JPGfilesellsfor\$69million,as“NFTmania”gatherspace.(2021).https://www.nytimes.com/2021/03/11/arts/design/ nft-auction-christies-beeple.html. (Accessed 4 May 2021). (The New York Times). 10. Phillips, D. The 10 most expensive NFTs ever sold. (2021). https://decrypt.co/62898/the-10-most-expensive-nfts-ever-sold. (Accessed 20 May 2021). (Decrypt). 11. Howcroft, E. “Cryptopunk” NFT sells for \$11.8 million at Sotheby’s. (2021). https://www.reuters.com/technology/cryptopunk- nft-sells-118-million-sothebys-2021-06-10/. (Accessed 25 June 2021). (Reuters). 12. Devlin,J.The“insane”moneyintradingcollectiblecards.(2021).https://www.bbc.co.uk/news/business-56413186.(Accessed20 May 2021). (BBC). 13. Wang, Q., Li, R., Wang, Q. & Chen, S. Non-fungible token (NFT): Overview, evaluation, opportunities and challenges. arXiv preprint arXiv:2105.07447 (2021). 14. Westerkamp,M.,Victor,F.&Küpper,A.Blockchain-basedsupplychaintraceability:Tokenrecipesmodelmanufacturingprocesses. in 2018 IEEE International Conference on Internet of Things (iThings) and IEEE Green Computing and Communications (GreenCom) and IEEE Cyber, Physical and Social Computing (CPSCom) and IEEE Smart Data (SmartData), 1595–1602 (IEEE, 2018). 15. Whitaker,A.Artandblockchain:Aprimer,history,andtaxonomyofblockchainusecasesintheArts.Artivate8,21–46(2019). 16. van Haaften-Schick, L. & Whitaker, A. From the artist’s contract to the blockchain ledger: New forms of artists’ funding using NFTs, fractional equity, and resale royalties. Available at SSRN 3842210, https://doi.org/10.2139/ssrn.3842210 (2021). 17. Serada,A.,Sihvonen,T.&Harviainen,J.T.CryptoKittiesandthenewludiceconomy:Howblockchainintroducesvalue,owner- ship, and scarcity in digital gaming. Games Culture 16, 457–480 (2021). 18. Sako, K., Matsuo, S. & Meier, S. Fairness in ERC token markets: A case study of CryptoKitties. arXiv preprint arXiv:2102.03721 (2021). 19. Dowling, M. Is non-fungible token pricing driven by cryptocurrencies? Finance Res. Lett. 102097, ISSN1544-6123. https://doi. org/10.1016/j.frl.2021.102097 (2021). 20. Dowling,M.Fertileland:Pricingnon-fungibletokens.FinanceRes.Lett.102096,https://doi.org/10.1016/j.frl.2021.102096(2021). 21. Franceschet,M.Artforspace.J.Comput.CulturalHeritage(JOCCH)13,1–9(2020). 22. Barabási,A.-L.TheArtmarketoftenworksinsecret.Here’salookinside.(2021).https://www.nytimes.com/2021/05/07/opinion/ nft-art-market.html. (Accessed 17 May 2021). (The New York Times). (2021) 11:20902 | https://doi.org/10.1038/s41598-021-00053-8 10PDF Image | Mapping the NFT revolution
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