Abstract—Internet financial news plays an important role in stock market forecasting. This paper discusses the relationship between the content of the Internet financial news and the yield of the stock market by using text mining technology and machine learning technology. The Latent Dirichlet distribution (LDA) model is used to analyze the Internet financial news. And the support vector machine (SVM) algorithm is used to predict the trend of the sector. Afterward constructs a trading strategy. The results show that the introduction of the information of tourism topic distribution in the Internet financial news can effectively improve the accuracy rate of forecast, thus increasing return of investment, especially when the stock market is in a volatile period. To sum up, the information of Internet.
 

Index Terms—internet financial news, stock market forecast, text mining, support vector machine

Cite: Jinxiao Wang, Jiaxin Shi, Dexin Han, and Xiaoyu Zhao, "Internet Financial News and Prediction for Stock Market: An Empirical Analysis of Tourism Plate Based on LDA and SVM," Journal of Advances in Information Technology, Vol. 10, No. 3, pp. 95-99, August 2019. doi: 10.12720/jait.10.3.95-99