Sentiment Analysis of China's Education Policy Online Opinion Based on Text Mining

Dan Zhang, Jie Zhang, Yuqing Zhang, Yuxin Wu
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引用次数: 2

Abstract

With the in-depth development of China's education reform, the combination of educational public opinion and emotion analysis is conducive to the discovery of the evolution law of public sentiment and related factors, and provides ideas for the guidance of public opinion of relevant government departments. This paper proposes an analysis model of public opinion on the education policy network based on text mining, obtains network comment contents through Octopus crawler, preprocesses the data, and introduces the calculation formula of emotion heat, on which the evolution process of public opinion is divided into incubation period, outbreak period, spreading period and decline period. Combined with visualization and emotional heat maps of provinces and ages are constructed, so as to grasp the spatial-temporal evolution law of educational public opinions. Taking the postponement of the college entrance examination in 2020 as an example, the empirical analysis proves that the online public opinion analysis model of education policy can reflect the evolution law.
基于文本挖掘的中国教育政策网络舆情分析
随着中国教育改革的深入开展,将教育舆情与情感分析相结合,有利于发现舆情演变规律及相关因素,为政府相关部门的舆论引导提供思路。本文提出了基于文本挖掘的教育政策网络舆情分析模型,通过章鱼爬虫获取网络评论内容,对数据进行预处理,引入情绪热度计算公式,将舆情的演变过程分为潜伏期、爆发期、传播期和衰退期。结合可视化和情感化的方法,构建各省、年龄段的热点图,掌握教育舆情的时空演变规律。以2020年高考延期为例,实证分析证明教育政策的网络舆情分析模型能够反映演进规律。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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