Sentiment Classification of Bitcoin-Related Tweets Using VADER: Analyzing Temporal Sentiment Trends in Cryptocurrency Markets

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Minh Luan Doan

Abstract

This study explores the intricate relationship between public sentiment and Bitcoin market dynamics, leveraging sentiment analysis of Twitter data to uncover patterns in emotional discourse surrounding cryptocurrency. By analyzing sentiment trends from 2013 to 2019, the research reveals a cyclical interplay between positive and negative sentiment, often aligning with Bitcoin’s dramatic price movements. Positive sentiment peaks coincide with periods of market optimism, driven by narratives of technological innovation and mainstream adoption, while negative sentiment troughs reflect moments of fear, uncertainty, and doubt (FUD) during market corrections. Despite the observed alignment, the correlation between sentiment and Bitcoin prices remains weak, underscoring the complexity of market behavior and the influence of external factors such as macroeconomic trends and regulatory developments. The findings highlight the potential of sentiment analysis as a complementary tool for market prediction, offering valuable insights into the emotional undercurrents that shape cryptocurrency markets. This study contributes to a deeper understanding of the socio-economic and psychological dimensions of Bitcoin, providing a foundation for future research in sentiment-driven market analysis.

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How to Cite
Doan, M. L. (2025). Sentiment Classification of Bitcoin-Related Tweets Using VADER: Analyzing Temporal Sentiment Trends in Cryptocurrency Markets. Journal of Current Research in Blockchain, 2(2), 88–102. https://doi.org/10.47738/jcrb.v2i2.31
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Articles