Bilateral Association Mining with Machine Learning to Predict Bitcoin Price Changing Trends

In this paper, we attempt to predict the price of Bitcoin from the emotion changes of investors and sentiment analysis is implemented to reflect the public response toward the Bitcoin market fluctuation. Meanwhile, the impact of the price variation on people ' s mood are discussed and abstracted into a backward prediction model. By establishing a closed-loop association mining network, this paper deeply explores the bi-directional interaction between the investor emotion and the bitcoin price, and with the help of this bilateral model, more decisive factors in changing the bitcoin price are considered. Consequently, the price tendency can be more accurately predicted. Compared with the existing bitcoin price prediction method, our network has higher degree of preciseness and robustness.