Emoji Driven Crypto Assets Market Reactions

Xiaorui Zuo, Yao-Tsung Chen, Wolfgang Karl Härdle
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Abstract

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.
表情符号驱动的加密资产市场反应
在蓬勃发展的加密货币领域,Twitter 等社交媒体平台已成为影响市场趋势和投资者情绪的关键。在我们的研究中,我们利用 GPT-4 和基于变换器的微调 BERT 模型进行多模态情感分析,重点研究表情符号对加密货币市场的影响。通过将表情符号转化为可量化的情绪数据,我们将这些见解与 BTCPrice 和 VCRIX 指数等关键市场指标相关联。这种方法可用于制定交易策略,旨在利用社交媒体元素识别和预测市场趋势。最重要的是,我们的研究结果表明,基于表情符号情绪的策略有助于避免市场大幅下滑,并有助于稳定回报。这项研究强调了将先进的人工智能驱动分析整合到金融策略中的实际好处,在学术背景下为数字通信与市场动态之间的相互作用提供了一个细致入微的视角。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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