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KryptoOracle: A Real-Time Cryptocurrency Price Prediction Platform Using Twitter Sentiments

Author

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  • Shubhankar Mohapatra
  • Nauman Ahmed
  • Paulo Alencar

Abstract

Cryptocurrencies, such as Bitcoin, are becoming increasingly popular, having been widely used as an exchange medium in areas such as financial transaction and asset transfer verification. However, there has been a lack of solutions that can support real-time price prediction to cope with high currency volatility, handle massive heterogeneous data volumes, including social media sentiments, while supporting fault tolerance and persistence in real time, and provide real-time adaptation of learning algorithms to cope with new price and sentiment data. In this paper we introduce KryptoOracle, a novel real-time and adaptive cryptocurrency price prediction platform based on Twitter sentiments. The integrative and modular platform is based on (i) a Spark-based architecture which handles the large volume of incoming data in a persistent and fault tolerant way; (ii) an approach that supports sentiment analysis which can respond to large amounts of natural language processing queries in real time; and (iii) a predictive method grounded on online learning in which a model adapts its weights to cope with new prices and sentiments. Besides providing an architectural design, the paper also describes the KryptoOracle platform implementation and experimental evaluation. Overall, the proposed platform can help accelerate decision-making, uncover new opportunities and provide more timely insights based on the available and ever-larger financial data volume and variety.

Suggested Citation

  • Shubhankar Mohapatra & Nauman Ahmed & Paulo Alencar, 2020. "KryptoOracle: A Real-Time Cryptocurrency Price Prediction Platform Using Twitter Sentiments," Papers 2003.04967, arXiv.org.
    • Handle: RePEc:arx:papers:2003.04967
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    References listed on IDEAS

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    1. Ziaul Haque Munim & Mohammad Hassan Shakil & Ilan Alon, 2019. "Next-Day Bitcoin Price Forecast," JRFM, MDPI, vol. 12(2), pages 1-15, June.
    2. Daniel Kahneman & Amos Tversky, 2013. "Prospect Theory: An Analysis of Decision Under Risk," World Scientific Book Chapters, in: Leonard C MacLean & William T Ziemba (ed.), HANDBOOK OF THE FUNDAMENTALS OF FINANCIAL DECISION MAKING Part I, chapter 6, pages 99-127, World Scientific Publishing Co. Pte. Ltd..
    3. Yhlas Sovbetov, 2018. "Factors Influencing Cryptocurrency Prices: Evidence from Bitcoin, Ethereum, Dash, Litcoin, and Monero," Journal of Economics and Financial Analysis, Tripal Publishing House, vol. 2(2), pages 1-27.
    4. Paul C. Tetlock, 2007. "Giving Content to Investor Sentiment: The Role of Media in the Stock Market," Journal of Finance, American Finance Association, vol. 62(3), pages 1139-1168, June.
    5. Brian M. Lucey & Michael Dowling, 2005. "The Role of Feelings in Investor Decision‐Making," Journal of Economic Surveys, Wiley Blackwell, vol. 19(2), pages 211-237, April.
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    Cited by:

    1. Jacques Vella Critien & Albert Gatt & Joshua Ellul, 2022. "Bitcoin price change and trend prediction through twitter sentiment and data volume," Financial Innovation, Springer;Southwestern University of Finance and Economics, vol. 8(1), pages 1-20, December.

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