论文标题
通过COVID-19大流行的各个阶段在中国跟踪公众舆论
Tracking Public Opinion in China through Various Stages of the COVID-19 Pandemic
论文作者
论文摘要
最近几个月，Covid-19已成为全球大流行，并对世界产生了巨大影响。在不同条件下的人们对流行病的态度截然不同。由于社交媒体的实时和大规模性质，我们可以不断从社交媒体获得与流行病有关的大量公众舆论信息。特别是，研究人员可能会提出诸如“大流行不同阶段的公众对中国对Covid-19的反应如何？”，“哪些因素会影响中国的公众舆论取向？”等问题。为了回答此类问题，我们分析了有关中国最大的社交媒体平台微博的大流行与公众舆论信息。具体而言，我们首先收集了大量与19009年相关的公众舆论微博。然后，我们使用情感分类器来识别和分析不同用户的观点。在以情感为导向的微博中，我们试图通过COVID-19大流行的不同阶段来跟踪公众舆论。此外，我们分析了可能影响Covid-19的公众舆论的更多关键因素（例如，不同省份的用户或具有不同教育水平的用户）。经验结果表明，公众的意见与Covid-19的关键因素不同。此外，我们分析了公众对不同公开概念主题的态度，例如呆在家里和隔离。
In recent months, COVID-19 has become a global pandemic and had a huge impact on the world. People under different conditions have very different attitudes toward the epidemic. Due to the real-time and large-scale nature of social media, we can continuously obtain a massive amount of public opinion information related to the epidemic from social media. In particular, researchers may ask questions such as "how is the public reacting to COVID-19 in China during different stages of the pandemic?", "what factors affect the public opinion orientation in China?", and so on. To answer such questions, we analyze the pandemic related public opinion information on Weibo, China's largest social media platform. Specifically, we have first collected a large amount of COVID-19-related public opinion microblogs. We then use a sentiment classifier to recognize and analyze different groups of users' opinions. In the collected sentiment orientated microblogs, we try to track the public opinion through different stages of the COVID-19 pandemic. Furthermore, we analyze more key factors that might have an impact on the public opinion of COVID-19 (e.g., users in different provinces or users with different education levels). Empirical results show that the public opinions vary along with the key factors of COVID-19. Furthermore, we analyze the public attitudes on different public-concerning topics, such as staying at home and quarantine.
