基于大数据的中国两个地区疫情舆论与政策比较分析

IF 0.9 4区 计算机科学 Q4 COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE
Dong Qiu, Lin Huang
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引用次数: 0

摘要

新冠肺炎疫情发生以来,中国政府采取了严格的防控措施。虽然疫情蔓延得到控制,但人们的日常生活和工作受到了不同程度的影响和限制。因此,人们有不同的情绪,这些可能会影响人们对政策的执行和遵守,从而影响疫情防控的有效性。目前,很少有文献分析人们的情感、政策和疫情趋势之间的关系。本文的目的是分析社交媒体上的文本内容,找出疫情封锁政策对公众情绪的影响和公众对政策变化表达的关注,以及疫情不同阶段政策与疫情状态的互动关系。在本文中,我们收集了两个同时发生疫情的城市的岗位进行分析和比较研究。我们一方面揭示了疫情期间两地公众关注和态度的变化,另一方面也反映了两地公众情绪的差异,以及在不同情况下采取不同政策时,情绪与政策、疫情趋势之间的相关性。所得结果对公共卫生部门制定合理的防疫政策具有一定的指导意义。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Comparative analysis of epidemic public opinion and policies in two regions of China based on big data
Since the outbreak of COVID-19 (Corona Virus Disease 2019), the Chinese government has taken strict measures to prevent and control the epidemic. Although the spread of the virus has been controlled, people’s daily life and work have been affected and restricted to varying degrees. Thus people have different sentiments, these may affect people’s implementation and compliance with the policies, thus affecting the effectiveness of epidemic prevention and control. At present, few pieces of literature have analyzed the relationships between people’s feelings, policies, and epidemic trends. The object of this paper is to analyze the text content on social media, to find out the impact of the epidemic blockade policy on the public mood and the concerns expressed by the public about policies changes, and the interaction between policies and epidemic states at different stages of the epidemic. In this paper, we collected the posts of two cities where the epidemic occurred at the same time for analysis and comparative study. On the one hand, we revealed the changes in public attention and attitudes in the two regions during the epidemic, the other hand, it also reflects the differences in public sentiment between the two regions, as well as the correlation between emotions and policies and epidemic trends when different policies are adopted under different circumstances. The obtained results have a certain guiding significance for public health departments to formulate reasonable epidemic prevention policies.
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来源期刊
Intelligent Data Analysis
Intelligent Data Analysis 工程技术-计算机:人工智能
CiteScore
2.20
自引率
5.90%
发文量
85
审稿时长
3.3 months
期刊介绍: Intelligent Data Analysis provides a forum for the examination of issues related to the research and applications of Artificial Intelligence techniques in data analysis across a variety of disciplines. These techniques include (but are not limited to): all areas of data visualization, data pre-processing (fusion, editing, transformation, filtering, sampling), data engineering, database mining techniques, tools and applications, use of domain knowledge in data analysis, big data applications, evolutionary algorithms, machine learning, neural nets, fuzzy logic, statistical pattern recognition, knowledge filtering, and post-processing. In particular, papers are preferred that discuss development of new AI related data analysis architectures, methodologies, and techniques and their applications to various domains.
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