近几十年来，神经网络发展迅速，现如今已经有了上百个神经网络模型，科研工作者也越发重视其价值。随着互联网的快速发展，数据量急剧增大，其中，短文本数据信息已经成为了互联网平台数据信息的重要组成部分。如何有效地对短文本信息进行分类、挖掘隐藏信息，也成为了许多企业、科研工作者的关注对象。针对这些现象，本文对神经网络的发展历程，模型的研究和发展现状等进行系统性梳理，并以文本数据为例，展示神经网络在文本分类问题上的应用及展望。

In recent decades, with the rapid development of neural network, now there have been hundreds of neural network models, researchers also pay more and more attention to its value. With the rapid development of the Internet, the amount of data increases rapidly, among which, short text data information has become an important part of the data information of the Internet platform. How to effectively classify short text information and excavate hidden information has also become the focus of many enterprises and researchers. In view of these phenomena, this paper systematically summarizes the history of neural network development, the research and development status of the model, and takes text data as an example to show the application and prospect of neural network in text classification.