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Price Movement Prediction of Cryptocurrencies Using Sentiment Analysis and Machine Learning

Tecnologico de Monterrey, Escuela de Ingeniería y Ciencias, Ave. Epigmenio González 500, Fracc. San Pablo, Querétaro 76130, Mexico
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Entropy 2019, 21(6), 589; https://doi.org/10.3390/e21060589
Received: 13 May 2019 / Revised: 11 June 2019 / Accepted: 13 June 2019 / Published: 14 June 2019
(This article belongs to the Section Signal and Data Analysis)
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Abstract

Cryptocurrencies are becoming increasingly relevant in the financial world and can be considered as an emerging market. The low barrier of entry and high data availability of the cryptocurrency market makes it an excellent subject of study, from which it is possible to derive insights into the behavior of markets through the application of sentiment analysis and machine learning techniques for the challenging task of stock market prediction. While there have been some previous studies, most of them have focused exclusively on the behavior of Bitcoin. In this paper, we propose the usage of common machine learning tools and available social media data for predicting the price movement of the Bitcoin, Ethereum, Ripple and Litecoin cryptocurrency market movements. We compare the utilization of neural networks (NN), support vector machines (SVM) and random forest (RF) while using elements from Twitter and market data as input features. The results show that it is possible to predict cryptocurrency markets using machine learning and sentiment analysis, where Twitter data by itself could be used to predict certain cryptocurrencies and that NN outperform the other models. View Full-Text
Keywords: price movement; cryptocurrencies; sentiment analysis; machine learning price movement; cryptocurrencies; sentiment analysis; machine learning
This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited (CC BY 4.0).
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MDPI and ACS Style

Valencia, F.; Gómez-Espinosa, A.; Valdés-Aguirre, B. Price Movement Prediction of Cryptocurrencies Using Sentiment Analysis and Machine Learning. Entropy 2019, 21, 589.

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