Social Networks and Railway Passenger Capacity: An Empirical Study Based on Text Mining and Deep Learning

Railway passenger transport is essential to modern transportation in China. The prediction of railway passenger capacity is of vital importance for ensuring the safety of railway transportation. This paper introduces social network text data into the prediction of railway passenger capacity. In the process of analyzing social network text data, text mining methods are used to analyze the text data, and the information related to railway passenger flow is extracted from the text and added to the prediction model. Meanwhile, in order to obtain better prediction results, this paper applies deep learning method on the data. The combination of text mining and deep learning method has greatly improved the accuracy of our prediction model. Experimental results show that a good accuracy rate has been achieved.