Zixiong Wang, Qiuying Chen, Sang-Joon Lee*
CMC-Computers, Materials & Continua, Vol.75, No.2, pp. 2443-2459, 2023, DOI:10.32604/cmc.2023.037553
Abstract The rapid expansion of the non-fungible token (NFT) market has attracted many investors. However, studies on the NFT price fluctuations have been relatively limited. To date, the machine learning approach has not been used to demonstrate a specific error in NFT sale price fluctuation prediction. The aim of this study was to develop a prediction model for NFT price fluctuations using the NFT trading information obtained from OpenSea, the world’s largest NFT marketplace. We used Python programs to collect data and summarized them as: NFT information, collection information, and related account information. AdaBoost and Random Forest (RF) algorithms were employed… More >
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