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Hot News Prediction Method Based on Natural Language Processing Technology and Its Application

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Abstract

In today’s era of information expansion, there exist a lot of real-time news every day, and there will be a time difference between potential real-time hotspots and hot news. It is time-consuming for IT operators to read all the real-time news and find the hot spots by human effort. Therefore, the prediction of hot news is particularly important for we-media operation. Therefore, this paper attempts to use natural language processing technology to predict hot news and to assist operators to create articles about the hot news. For hot news prediction, this paper proposes a method of data preprocessing and uses several models based on convolutional neural networks (CNNs), text convolutional neural networks (TextCNNs), long-short term memory (LSTM), bi-directional long short-term memory (BiLSTM) to train. We also build a new model—CNN Distinct and BiLSTM Extract, which can be called CDBE for short—to obtain better performance. We evaluate several training models and analyze them by multiple evaluation indexes. In addition, we apply the method proposed in this paper to actual operation work, and the result shows that such can greatly reduce operators’ pressure, save the working time for creating articles about hot news, and greatly improve their work efficiency.

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Funding

This work is supported by the Natural Science Foundation Project of China (61976118) and the Natural Science Foundation Project of Jiangsu Province (BK20180142).

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Authors and Affiliations

  1. College of Information Engineering, Nanjing XiaoZhuang University, 211171, Jiangsu, China

    Yiqin Bao & Hao Zheng

  2. School of Computer Science and Technology, Heilongjiang University, 150080, Harbin, China

    Zhengtang Sun

  3. Schulich School of Business, 416647, Toronto, Canada

    Qiang Zhao

  4. Alibaba Cloud University, 310001, Zhejiang, China

    Qiang Zhao

  5. College of Optical Engineering, Zhejiang University of Technology, 321006, Zhejiang, China

    Tianya Lin

  6. Nanjing Suta Intelligent Technology Co., LTD, 210003, Jiangsu, China

    Yiqin Bao

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  1. Yiqin Bao
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  2. Zhengtang Sun
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  3. Qiang Zhao
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  4. Tianya Lin
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  5. Hao Zheng
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Correspondence to Yiqin Bao.

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Yiqin Bao, Sun, Z., Zhao, Q. et al. Hot News Prediction Method Based on Natural Language Processing Technology and Its Application. Aut. Control Comp. Sci. 56, 83–94 (2022). https://doi.org/10.3103/S0146411622010023

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