Bitcoin Price Prediction using Twitter Sentiment Analysis

Authors

  • Himanshu Bute Symbiosis Institute of Technology, (Pune campus), symbiosis International Deemed University, Pune 411215, India
  • Abhyuday Singh Symbiosis Institute of Technology, (Pune campus), symbiosis International Deemed University, Pune 411215, India
  • Shlok Nandurbarkar Symbiosis Institute of Technology, (Pune campus), symbiosis International Deemed University, Pune 411215, India
  • Shivali Amit Wagle Symbiosis Institute of Technology, (Pune campus), symbiosis International Deemed University, Pune 411215, India
  • Preksha Pareek Symbiosis Institute of Technology, (Pune campus), symbiosis International Deemed University, Pune 411215, India

Keywords:

Bitcoin, Sentiment analysis, preprocessing

Abstract

This work explores predicting Bitcoin prices using sentiment analysis on Twitter. Leveraging machine learning and rule-based methods, the study correlates social media sentiment, especially on Twitter, with dynamic Bitcoin prices. The dataset combines historical Bitcoin prices from Yahoo Finance and relevant Twitter data. Preprocessing involves cleaning tweets, calculating sentiment scores, and merging datasets. Results indicate that SGD regression and ridge regression achieve the best performance with a Validation-MAPE of 8.45%. Despite Bitcoin's volatility, the study highlights the potential of sentiment analysis in forecasting values, shedding light on the intricate relationship between social media sentiments and cryptocurrency markets.

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References

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Published

23.02.2024

How to Cite

Bute, H. ., Singh, A. ., Nandurbarkar, S. ., Wagle, S. A. ., & Pareek, P. . (2024). Bitcoin Price Prediction using Twitter Sentiment Analysis. International Journal of Intelligent Systems and Applications in Engineering, 12(17s), 469–477. Retrieved from https://ijisae.org/index.php/IJISAE/article/view/4906

Issue

Vol. 12 No. 17s (2024)

Section

Research Article

License

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