Twitter Sentiment Analysis on Bitcoin Price

Mingyuan Li

doi:10.54254/2754-1169/101/20231593

Research Article

Open access

Published on 25 July 2024

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Li,M. (2024). Twitter Sentiment Analysis on Bitcoin Price. Advances in Economics, Management and Political Sciences,101,171-180.

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Twitter Sentiment Analysis on Bitcoin Price

Mingyuan Li *^,1,

¹ School of Engineering, Vanderbilt University, Nashville, Tennessee 37235, United States

* Author to whom correspondence should be addressed.

https://doi.org/10.54254/2754-1169/101/20231593

Abstract

The price of cryptocurrency can be affected by several factors these years, such as technology, social media, COVID-19, etc. One of the examples of these factors is Elon Mask’s tweets about cryptocurrency, which help to increase cryptocurrency prices. With the spread of the epidemic, people are restricted from meeting in person. Therefore, more and more people are active on online social media sites such as Twitter. This research wants to determine if tweets related to cryptocurrency (Bitcoin, one of the most popular cryptocurrencies nowadays) affect price. By taking 5 machine learning models and the Granger causality test, the correlation and causation relationship between sentiment analysis and bitcoin price can be determined.

Keywords

cryptocurrency, sentiment analysis, machine learning, granger causality test

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Cite this article

Li,M. (2024). Twitter Sentiment Analysis on Bitcoin Price. Advances in Economics, Management and Political Sciences,101,171-180.

Data availability

The datasets used and/or analyzed during the current study will be available from the authors upon reasonable request.

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About volume

Volume title: Proceedings of the 2nd International Conference on Financial Technology and Business Analysis

Conference website: https://2023.icftba.org/

ISBN：978-1-83558-525-2(Print) / 978-1-83558-526-9(Online)

Conference date: 8 November 2023

Editor：Javier Cifuentes-Faura

Series: Advances in Economics, Management and Political Sciences

Volume number: Vol.101

ISSN：2754-1169(Print) / 2754-1177(Online)

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