基于自然语言处理的COVID-19反弹分析

2021 6th International Conference on Intelligent Computing and Signal Processing (ICSP) Pub Date : 2021-04-09 DOI:10.1109/ICSP51882.2021.9408930

R. Tang, Lei Zhang, Guangbin Zhang, Jiaqi Wang

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引用次数: 0

摘要

全球新型冠状病毒疫情尚未结束。患这种疾病的人数不断增加。此外，人们在网站上发表了一些评论，这可能与疫情有关。本文将对这种关系进行分析，并对各国政府提出一些建议。首先，利用爬虫获取公众情绪数据。NLP是这项工作的主要方法，它可以根据情感词典对我们得到的单词进行分类。最后，我们做了进一步的分析，并通过回归给出了确诊病例的警戒线，其值在30人左右。

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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Analysis of COVID-19 Rebound Based on Natural Language Processing

The novel coronavirus epidemic hasn't finished in the world. The number of people who come down with this disease keeps increasing. Besides, people make some comments on the website, which may be related to the epidemic situation. This work will analyze this relationship and make some suggestions to governments. First, the crawler is used to get the data of public emotion. NLP is the main method in this work, which can classify the words we get based on an emotion dictionary. In the end, we do some further analysis and give the warning line of confirmed cases by regression, whose value is around 30 people.

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2021 6th International Conference on Intelligent Computing and Signal Processing (ICSP)

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