Analysis of the Impact of Market Sentiment on NFT Pricing Using Data Analytics Techniques

Abstract

The recent surge in Non-Fungible Tokens (NFTs) has changed the way digital assets have been valued. Of late, market sentiment has become essential in price determination. This study provides insights into this intricate nexus between NFT prices and market sentiments by use of data analytics. We convert categorical NFT variables into sentiment proxies using Pythonbased data preprocessing, visualization, and machine learning models to gauge their effect on price variability. Using Random Forest and Linear Regression as models, the comparison shows that market sentiment affects price variability considerably. Our work advances a noble cause of transparency in decision-making among investors by empowering those who navigate the unstable NFT ecosystem with data-developed perspectives.