Twitter Sentiment Analysis for Bitcoin Price Prediction

2023 3rd International Conference on Smart Data Intelligence (ICSMDI) Pub Date : 2023-03-01 DOI:10.1109/ICSMDI57622.2023.00015

Achyut Jagini, Kaushal Mahajan, Namita Aluvathingal, Vedanth Mohan, Prajwala Tr

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引用次数: 1

Abstract

Cryptocurrencies, like Bitcoin, have become increasingly popular over the last decade. The price of Bitcoin has gone through several cycles of highs and lows. As a result, it is a widely discussed topic, especially on platforms like Twitter. Sentiment analysis is a research area of Natural Language Processing. It is used to determine whether the text is positive, negative, or neutral. Twitter tweets are more challenging to analyze when compared to other forms of text, due to the presence of irregular grammar, emoticons, and sarcasm. This study intends to analyze the effect of tweets on the stock price of Bitcoin. In order to study the effect, the sentiment associated with each tweet is calculated using VADER, and also the profession and follower count associated with verified users who tweet about bitcoin is found. Following this, a model is trained and tested using a combined dataset of tweet related data and historical bitcoin price data. It was found that the sentiment of tweets does correlate with the shift in the price of bitcoin.

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推特情绪分析预测比特币价格

比特币等加密货币在过去十年中变得越来越受欢迎。比特币的价格已经经历了几个高点和低点的周期。因此，这是一个广泛讨论的话题，尤其是在Twitter等平台上。情感分析是自然语言处理的一个研究领域。它用于确定文本是肯定的、否定的还是中性的。由于存在不规则语法、表情符号和讽刺，与其他形式的文本相比，Twitter的推文更具挑战性。本研究旨在分析推文对比特币股价的影响。为了研究效果，使用VADER计算与每条推文相关的情绪，并找到与发布比特币推文的验证用户相关的职业和关注者数量。在此之后，使用tweet相关数据和历史比特币价格数据的组合数据集训练和测试模型。研究发现，推文的情绪确实与比特币价格的变化有关。

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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2023 3rd International Conference on Smart Data Intelligence (ICSMDI)

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