Author(s)

Shanyun Li

Corresponding Author

Shanyun Li

Abstract

The article combines historical news data and historical data of bitcoin and the stock market, performs natural language processing on the news data and reads text information, uses sentiment processing to determine the positive and negative news sentiment, digitizes the news, and combines historical data of the stock market and bitcoin. R language is used for ridge regression, linear regression, logistic regression, random forest, XGBoost and other data analysis to predict the trend and price of Bitcoin.

Keywords

Bitcoin; Prediction; model; R Language; machine Learning