Emoji Driven Crypto Assets Market Reactions
Xiaorui Zuo Yao-Tsung Chen Wolfgang Karl Härdle
In the burgeoning realm of cryptocurrency, social media platforms like
Twitter have become pivotal in influencing market trends and investor
sentiments. In our study, we leverage GPT-4 and a fine-tuned transformer-based
BERT model for a multimodal sentiment analysis, focusing on the impact of emoji
sentiment on cryptocurrency markets. By translating emojis into quantifiable
sentiment data, we correlate these insights with key market indicators like BTC
Price and the VCRIX index. This approach may be fed into the development of
trading strategies aimed at utilizing social media elements to identify and
forecast market trends. Crucially, our findings suggest that strategies based
on emoji sentiment can facilitate the avoidance of significant market downturns
and contribute to the stabilization of returns. This research underscores the
practical benefits of integrating advanced AI-driven analyses into financial
strategies, offering a nuanced perspective on the interplay between digital
communication and market dynamics in an academic context.