Predictors of Nfts Prices : An Automated Machine Learning Approach

This article uses automated machine learning to discover the most relevant determinants of non-fungible tokens (NFT) prices. NFTs pricing is affected by several internal and external factors, including market conditions, network factors, and NFTs features. Automated Machine Learning (AML) is a suitable technique to investigate the most impactful factors due to a lack of knowledge on the exact determinants. Analyzing a comprehensive dataset with 16 features and over 19,183 data points on NFT prices and NFT social communities with a random forest model, we find that network factors are the most important pricing determinants: Twitter members followed by Discord members