Proceedings of the 3rd International Conference on Digital Economy and Computer Application (DECA 2023)

Research on Tweet Sentiment Analysis Based on VADER in the Field of Cryptocurrency

Authors
Ji Miao1, *
1College of Information Science and Technology, Hangzhou Normal University, Hangzhou, Zhejiang Province, 310036, China
*Corresponding author. Email: 1060150683@qq.com
Corresponding Author
Ji Miao
Available Online 4 December 2023.
DOI
10.2991/978-94-6463-304-7_28How to use a DOI?
Keywords
Cryptocurrency; Opinion Risk Monitoring; Sentiment Analysis; VADER; Cross-correlation Analysis
Abstract

This research aims to develop a tool to assess the impact of social media on the market by collecting and analyzing cryptocurrency-related tweets on Twitter. Python and relevant libraries are utilized for scraping tweets and cryptocurrency trading data, followed by data preprocessing. The VADER model is then employed for sentiment analysis of the tweets, extracting sentiment polarity and intensity. Considering the influence of tweets, an overall sentiment score is calculated.

Copyright
© 2023 The Author(s)
Open Access
Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

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Volume Title
Proceedings of the 3rd International Conference on Digital Economy and Computer Application (DECA 2023)
Series
Atlantis Highlights in Computer Sciences
Publication Date
4 December 2023
ISBN
10.2991/978-94-6463-304-7_28
ISSN
2589-4900
DOI
10.2991/978-94-6463-304-7_28How to use a DOI?
Copyright
© 2023 The Author(s)
Open Access
Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

Cite this article

TY  - CONF
AU  - Ji Miao
PY  - 2023
DA  - 2023/12/04
TI  - Research on Tweet Sentiment Analysis Based on VADER in the Field of Cryptocurrency
BT  - Proceedings of the 3rd International Conference on Digital Economy and Computer Application (DECA 2023)
PB  - Atlantis Press
SP  - 256
EP  - 264
SN  - 2589-4900
UR  - https://doi.org/10.2991/978-94-6463-304-7_28
DO  - 10.2991/978-94-6463-304-7_28
ID  - Miao2023
ER  -