Predicting Bitcoin price changes using sentiment analysis in social media and celebrities along with data mining

Qorbani, Ali; Rabbani, Yousef; Kamran Rad, Reza; Falsafi, Peyman

doi:10.22075/jem.2023.28817.1772

Predicting Bitcoin price changes using sentiment analysis in social media and celebrities along with data mining

Document Type : Original Article

Authors

Ali Qorbani ¹

Yousef Rabbani ²

Reza Kamran rad ²

peyman Falsafi ¹

¹ MSc. Student in Industrial Engineering, Engineering Department, Semnan University, Semnan, Iran

² Assistant Professor in Industrial Engineering, Engineering Department, Semnan University, Semnan-Iran

10.22075/jem.2023.28817.1772

Abstract

Most of the research has been done on predicting the price changes of cryptocurrencies, and the researchers used machine learning algorithms in this field. The purpose of this article is to present an approach to predicting Bitcoin price changes using machine learning algorithms along with data from people's sentiment analysis towards famous people such as Elon Musk on Twitter, Reddit, and Telegram social networks. The data collected for this research is from 2021 and 2022. The distinguishing feature of this research is the use of technical, economic indicators and sentiment analysis simultaneously to predict the price trend. The recursive feature removal method was used to select the feature and in the next step, the results were compared by testing 8 classification algorithms. In this research, the xgboost algorithm showed excellent performance with a record accuracy of 88% in predicting the trend of Bitcoin price changes.

Keywords

Bitcoin

cryptocurrency

sentiment analysis

machine learning algorithms