Bitcoin price prediction using keyword search volumes and tweet information

Abstract

In this paper, we propose an LSTM for predicting Bitcoin price using Google Trends data and sentiment scores of news and tweets. We used sentiment scores of news weighted by the number of news as inputs. We also used sentiment scores of tweet sentiment scores weighted by tweet information, such as the number of likes, the number of retweets and the number of followers and used them as inputs. The results show better performance of the proposed method than using the non-weighted sentiment scores of news and tweets as inputs.