Open Access

ARTICLE

Predicting Bitcoin Trends Through Machine Learning Using Sentiment Analysis with Technical Indicators

Hae Sun Jung¹, Seon Hong Lee¹, Haein Lee¹, Jang Hyun Kim^2,*

1 Department of Applied Artificial Intelligence/Department of Human-Artificial Intelligence Interaction, Sungkyunkwan University, Seoul, 03063, Korea
2 Department of Interaction Science/Department of Human-Artificial Intelligence Interaction, Sungkyunkwan University, Seoul, 03063, Korea

* Corresponding Author: Jang Hyun Kim. Email:

Computer Systems Science and Engineering 2023, 46(2), 2231-2246. https://doi.org/10.32604/csse.2023.034466

Received 18 July 2022; Accepted 10 October 2022; Issue published 09 February 2023

Abstract

Predicting Bitcoin price trends is necessary because they represent the overall trend of the cryptocurrency market. As the history of the Bitcoin market is short and price volatility is high, studies have been conducted on the factors affecting changes in Bitcoin prices. Experiments have been conducted to predict Bitcoin prices using Twitter content. However, the amount of data was limited, and prices were predicted for only a short period (less than two years). In this study, data from Reddit and LexisNexis, covering a period of more than four years, were collected. These data were utilized to estimate and compare the performance of the six machine learning techniques by adding technical and sentiment indicators to the price data along with the volume of posts. An accuracy of 90.57% and an area under the receiver operating characteristic curve value (AUC) of 97.48% were obtained using the extreme gradient boosting (XGBoost). It was shown that the use of both sentiment index using valence aware dictionary and sentiment reasoner (VADER) and 11 technical indicators utilizing moving average, relative strength index (RSI), stochastic oscillators in predicting Bitcoin price trends can produce significant results. Thus, the input features used in the paper can be applied on Bitcoin price prediction. Furthermore, this approach allows investors to make better decisions regarding Bitcoin-related investments.

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Keywords

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