From Tweets to Trades: An Investigation into the Impact of NFT Project Twitters on Market Liquidity

Abstract

Amid the rapid expansion of the Non-Fungible Token (NFT) market, X (formerly Twitter) has emerged as a crucial channel for communication between project creators and their communities. This study investigates the short-term effects of NFT project tweets on trading behaviors and price dynamics. Guided by Media Richness Theory (MRT), we con-ducted a quantitative analysis of tweets from nine leading NFT projects, categorizing them into three distinct clusters. Our findings reveal heterogeneous correlations between tweet content, NFT categories, and price fluctuations. The differing roles and functions of NFTs across categories shape both the distribution of tweets and their short-term pricing impacts. Furthermore, we employed three machine learning models using media richness as a predictive feature, achieving approximately 60 % accuracy in forecasting NFT price movements. Overall, this research highlights the predictive potential of social media for NFT price trends and its contribution to the NFT ecosystems sustainability.