基于情绪共识聚类(SCC)的COVID-19期间BTC走势分析

2021 IEEE 12th Annual Information Technology, Electronics and Mobile Communication Conference (IEMCON) Pub Date : 2021-10-27 DOI:10.1109/iemcon53756.2021.9623182

A. Ibrahim

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引用次数: 0

摘要

来自社交媒体的推文可以帮助提供商业领域市场情绪的早期迹象。意见挖掘和机器学习可以用来发现潜在的情绪。推特人气与未来比特币价格变化之间存在联系。本文利用共识聚类的概念，利用在COVID-19时间框架内收集的推文来预测疫情爆发后比特币的早期走势。来自Twitter等具有不同属性、设置和程度的文本数据集的结果表明，所提出的共识方法在预测COVID-19大流行期间和之后的比特币趋势方面具有优势。

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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Analyzing BTC's Trend During COVID-19 Using A Sentiment Consensus Clustering (SCC)

Tweets from social media can help in providing an early sign of market mood in the business sector. Opinion mining and machine learning can be used to discover the underlying sentiment. There's a link between Twitter sentiment and Bitcoin price changes in the future. Using the concept of Consensus clustering, this paper leverages Tweets collected during the COVID-19 timeframe to forecast early Bitcoin movements following the outbreak. Results from text datasets such as Twitter with various attributes, settings, and degrees show the superiority of the proposed consensus approach in predicting the BTC trend during and after the COVID-19 pandemic.

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来源期刊

2021 IEEE 12th Annual Information Technology, Electronics and Mobile Communication Conference (IEMCON)

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