Abstract

Cryptocurrency is a form of digital currency using cryptographic techniques in a decentralized system for secure peer-to-peer transactions. It is gaining much popularity over traditional methods of payment because it facilitates very fast, easy, and secure transactions. Social media is a significant influence, but it is also very volatile and subject to a variety of other factors. Thus, with over four billion active users on social media, we need to understand its influence on the crypto market and how it can lead to fluctuations in the values of these cryptocurrencies. In our work, we analyze the influence of activities on Twitter, in particular the sentiments of the tweets posted regarding cryptocurrencies and how they influence their prices. In addition, we also collect metadata related to tweets and users. We try to leverage these features to predict the price of cryptocurrency, for which we use some regression-based models and an LSTM-based model.

中文翻译：

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加密货币市场分析的未来：社交媒体数据和用户元数据

 抽象的

加密货币是一种数字货币形式，在去中心化系统中使用加密技术来实现安全的点对点交易。它比传统支付方式更受欢迎，因为它促进非常快速、简单和安全的交易。社交媒体具有重大影响力，但它也非常不稳定，并受到各种其他因素的影响。因此，社交媒体上有超过 40 亿活跃用户，我们需要了解它对加密货币市场的影响以及它如何导致这些加密货币价值的波动。在我们的工作中，我们分析了 Twitter 上活动的影响，特别是发布的有关加密货币的推文的情绪以及它们如何影响其价格。此外，我们还收集与推文和用户相关的元数据。我们尝试利用这些特征来预测加密货币的价格，为此我们使用一些基于回归的模型和基于 LSTM 的模型。