Bitcoin Price Prediction Considering Sentiment Analysis on Twitter and Google News

Abstract

Cryptocurrencies are digital currencies that operate on the blockchain, which is the technology that offers security and decentralization. The principal characteristic of cryptocurrencies is that they are not generally issued by a central authority. Many factors can influence the volatility of prices. This paper enables to drive insights into the behavior of markets through the application of sentiment analysis of Tweets, Google news and machine learning techniques for the challenging task of cryptocurrency price prediction. Most of the studies have focused exclusively on the sentiment analysis of tweets. In this work, we propose the use of common machine learning tools and available Google News data for predicting the price of crypto. We present the results of the Long Short-Term Memory (LSTM) model using Tweets and Google News data.