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针对新冠疫苗讨论的情感分析与主题建模

Sentiment analysis and topic modeling for COVID-19 vaccine discussions.

作者信息

Yin Hui, Song Xiangyu, Yang Shuiqiao, Li Jianxin

机构信息

School of IT, Deakin University, Geelong, Australia.

School of Computer Science and Engineering, University of New South Wales, Sydney, Australia.

出版信息

World Wide Web. 2022;25(3):1067-1083. doi: 10.1007/s11280-022-01029-y. Epub 2022 Feb 25.

Abstract

The outbreak of the novel coronavirus disease (COVID-19) has been ongoing for almost two years and has had an unprecedented impact on the daily lives of people around the world. More recently, the emergence of the Delta variant of COVID-19 has once again put the world at risk. Fortunately, many countries and companies have developed vaccines for the coronavirus. As of 23 August 2021, more than 20 vaccines have been approved by the World Health Organization (WHO), bringing light to people besieged by the pandemic. The global rollout of the COVID-19 vaccine has sparked much discussion on social media platforms, such as the effectiveness and safety of the vaccine. However, there has not been much systematic analysis of public opinion on the COVID-19 vaccine. In this study, we conduct an in-depth analysis of the discussions related to the COVID-19 vaccine on Twitter. We analyze the hot topics discussed by people and the corresponding emotional polarity from the perspective of countries and vaccine brands. The results show that most people trust the effectiveness of vaccines and are willing to get vaccinated. In contrast, negative tweets tended to be associated with news reports of post-vaccination deaths, vaccine shortages, and post-injection side effects. Overall, this study uses popular Natural Language Processing (NLP) technologies to mine people's opinions on the COVID-19 vaccine on social media and objectively analyze and visualize them. Our findings can improve the readability of the confusing information on social media platforms and provide effective data support for the government and policy makers.

摘要

新型冠状病毒病(COVID-19)疫情已持续近两年,对全球人民的日常生活产生了前所未有的影响。最近,COVID-19德尔塔变种的出现再次使世界面临风险。幸运的是,许多国家和公司已经研发出了针对冠状病毒的疫苗。截至2021年8月23日,已有20多种疫苗获得世界卫生组织(WHO)批准,给受疫情困扰的人们带来了希望。COVID-19疫苗在全球的推广引发了社交媒体平台上的诸多讨论,比如疫苗的有效性和安全性。然而,对于COVID-19疫苗的公众舆论尚未有太多系统性分析。在本研究中,我们对推特上与COVID-19疫苗相关的讨论进行了深入分析。我们从国家和疫苗品牌的角度分析了人们讨论的热门话题以及相应的情感倾向。结果表明,大多数人相信疫苗的有效性并愿意接种。相比之下,负面推文往往与接种后死亡、疫苗短缺以及注射后副作用的新闻报道有关。总体而言,本研究运用流行的自然语言处理(NLP)技术挖掘社交媒体上人们对COVID-19疫苗的看法,并对其进行客观分析和可视化呈现。我们的研究结果可以提高社交媒体平台上纷繁信息的可读性,并为政府和政策制定者提供有效的数据支持。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7d5c/8879179/c2fa9a0885d8/11280_2022_1029_Fig1_HTML.jpg

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