International Conference on Computer and Knowledge Engineering

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Time Series Analysis by Bi-GRU for Forecasting Bitcoin Trends based on Sentiment Analysis

Authors :

Fatemeh Saadatmand¹ Mohammad Ali Zare Chahoki²

1- Computer Engineering Department, Yazd University, Yazd, Iran 2- Computer Engineering Department, Yazd University, Yazd, Iran

Keywords :

Bitcoin،Sentiment analysis،Cryptocurrencies،Bi-GRU

Abstract :

In the last few years, investors attracted a lot to cryptocurrency marketing, especially Bitcoin. This market has experienced extreme changes and this has made it a challenge to predict whether the price will rise or fall in the near or far future. One of the most challenging problems in this area is predicting the future price trend. Various factors affect the price of Bitcoin, such as: including public sentiments, the number of competing cryptocurrencies, media, and news. Twitter data as a source of public sentiment can be helpful to increase the accuracy of Bitcoin trend prediction. The purpose of this paper is to introduce a new approach to Bitcoin trend prediction using deep learning algorithms. By sentiment analysis of extracted data from Twitter and tracking the previous price. The data collected for this research is between January 2012 to December 2020. In this article, LSTM, BILSTM, GRU, and BiGRU algorithms are compared to predict the trend of Bitcoin price changes. The BiGRU algorithm better performance by registering a record of 72% accuracy in predicting the trend of Bitcoin price changes and improving 20% the speed of the learning process.

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