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Studying Public Perception about Vaccination: A Sentiment Analysis of Tweets

机译:研究公众对疫苗接种的看法:推文的情感分析

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摘要

Text analysis has been used by scholars to research attitudes toward vaccination and is particularly timely due to the rise of medical misinformation via social media. This study uses a sample of 9581 vaccine-related tweets in the period 1 January 2019 to 5 April 2019. The time period is of the essence because during this time, a measles outbreak was prevalent throughout the United States and a public debate was raging. Sentiment analysis is applied to the sample, clustering the data into topics using the term frequency–inverse document frequency (TF-IDF) technique. The analyses suggest that most (about 77%) of the tweets focused on the search for new/better vaccines for diseases such as the Ebola virus, human papillomavirus (HPV), and the flu. Of the remainder, about half concerned the recent measles outbreak in the United States, and about half were part of ongoing debates between supporters and opponents of vaccination against measles in particular. While these numbers currently suggest a relatively small role for vaccine misinformation, the concept of herd immunity puts that role in context. Nevertheless, going forward, health experts should consider the potential for the increasing spread of falsehoods that may get firmly entrenched in the public mind.
机译:文本分析已被学者用来研究对疫苗接种的态度,由于通过社交媒体发布的医疗错误信息的出现,文本分析特别及时。这项研究使用了从2019年1月1日到2019年4月5日的9581个与疫苗相关的推文样本。该时间段至关重要,因为在此期间,麻疹在美国各地盛行,公众辩论也在激烈进行。情感分析应用于样本,使用术语频率-文档反转频率(TF-IDF)技术将数据聚类为主题。分析表明,大多数(约77%)推文都集中在寻找针对埃博拉病毒,人乳头瘤病毒(HPV)和流感等疾病的新型疫苗。在其余的人中,约有一半与美国最近爆发的麻疹有关,约有一半是支持者与反对者之间针对麻疹疫苗的持续辩论的一部分。尽管目前这些数字表明疫苗错误信息的作用相对较小,但是群免疫的概念将这种作用置于背景之中。然而,展望未来,卫生专家应考虑可能会在公众心中根深蒂固的虚假信息蔓延的可能性。

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