Understanding NFT Price Moves through Tweets Keywords Analysis
Junliang Luo, Yongzheng Jia, Xue Liu

TL;DR
This paper investigates how Twitter community activity and specific keywords influence NFT price movements, demonstrating that social media data can effectively predict NFT price directions and magnitudes.
Contribution
It introduces a novel analysis of Twitter keywords' impact on NFT prices, combining causality tests and predictive modeling to uncover market-behavior insights.
Findings
Number of tweets Granger-causes NFT prices for most top projects.
Social media words significantly improve NFT price move predictions.
Market-related and event-related words positively influence price change predictions.
Abstract
Non-Fungible Token (NFT) is evolving with the rise of the cryptocurrency market and the development of blockchain techniques, which leads to an emerging NFT market that has become prosperous rapidly then followed by a cooldown. Nevertheless, the overall rise procedure of the NFT market has not been well understood. To this end, we consider that social media communities evolving alongside the market growth, are worth exploring and reasoning about, as the mineable information might unveil the market behaviors. We explore the procedure from the perspective of NFT Twitter communities and its impact on the NFT price moves with two experiments. We perform a Granger causality test on the number of tweets and the NFT price time series and find that the number of tweets has a positive impact on (Granger-causes) the price or reversely for larger part of the 19 top authentic projects but seldom…
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Taxonomy
TopicsBlockchain Technology Applications and Security · FinTech, Crowdfunding, Digital Finance · Spam and Phishing Detection
