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计算机工程 ›› 2019, Vol. 45 ›› Issue (3): 315-320. doi: 10.19678/j.issn.1000-3428.0049795

• 开发研究与工程应用 • 上一篇    

基于时间窗口的舆情异动量化模型

张阳,李雄飞   

  1. 吉林大学 计算机科学与技术学院,长春 130012
  • 收稿日期:2018-01-04 出版日期:2019-03-15 发布日期:2019-03-15
  • 作者简介:张阳(1992—),男,硕士研究生,主研方向为自然语言处理;李雄飞,教授、博士生导师。
  • 基金资助:

    中国博士后科学基金面上项目(2017M611323);吉林省优秀青年人才基金(20180520029JH)。

Quantitative Model of Public Opinion Change Based on Time Window

ZHANG Yang,LI Xiongfei   

  1. College of Computer Science and Technology,Jilin University,Changchun 130012,China
  • Received:2018-01-04 Online:2019-03-15 Published:2019-03-15

摘要:

现有互联网文本舆情分析模型多数未考虑时间因素的影响,对舆情动态变化过程缺乏定量刻画,难以准确发现舆情演化的动态过程和关键要素。为此,提出一种改进的舆情异动量化模型。通过线性回归模型得出不同时间窗口内的舆情静态表现,利用趋势线刻画舆情随时间的变化情况,结合舆情整体走势和异动角度获得舆情异动指数。基于国内A股涨跌预测的实验结果表明,与传统舆情分析模型相比,该模型具有更高的预测准确率和更好的稳定性。

关键词: 舆情值, 舆情异动指数, 时间窗口, 线性回归, 金融文本

Abstract:

Most of the existing Internet text public opinion analysis models do not consider the influence of time factors,and lack of quantitative description of the dynamic change process of public opinion,so it is difficult to accurately discover the dynamic process and key elements of public opinion evolution.Therefore,this paper proposes an improved quantitative model of public opinions change.Through the linear regression model,the static performance of the opinion in different time windows is obtained.The trend line is used to describe the change situation of the public opinion over time,and the public opinions change index is obtained by combining the overall trend and the change angle of the public opinion.Based on the fluctuated forecast of the domestic A-share stocks,experimental results show that the model has a higher prediction accuracy and stability than the traditional public opinion analysis model.

Key words: public opinion, public opinion change index, time window, linear regression, financial text

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