# Introduction

Financial markets have been volatile. Most of the time, market fluctuations are normal, but some fluctuations, due to sudden external shocks or other unexpected factors, exhibit abnormal conditions that are different from the normal pattern. These abnormal fluctuations, some of the markets can quickly digest, the other part may lead to a positive feedback amplification effect, relying solely on the invisible hand of the market is difficult to extricate themselves, and the real economy will also pay a heavy price for this[1]. Forecasting in various financial markets, including the stock market, has always attracted great interest from academic and business circles. But are financial markets predictable? Traditional finance is based on the random walk and efficient markets hypothesis. According to the efficient market hypothesis, stock prices move based on new information (news), not on past or future stock prices. The emergence of new information in the market is unpredictable, so stock prices are unpredictable [2]. However, in recent years, a lot of new work has begun to challenge the validity of the efficient market’s hypothesis, for example, from the behavioral finance perspective. Many studies also show that the financial market is not a completely random process, to some extent, there may be a certain degree of predictability in the financial market. For example, indeed, we cannot predict the emergence of new information in the market, but we can grasp some indicators from social networking media (Twitter, Facebook, other blogs, etc.) and use these indicators to predict future changes in mood and information in the economy and society to a certain extent [3-4]. Such work is already at play in the economy and society, such as using online chat data to predict book sales, using PLSA models to extract emotional information from blogs to predict movie ticket sales, and using Google search queries to predict the early spread and spread rate of influenza.