监测日本和印度尼西亚推特上对COVID-19疫苗副作用的提及:信息流行病学研究

IF 3.5 Q1 HEALTH CARE SCIENCES & SERVICES JMIR infodemiology Pub Date : 2022-07-01 DOI:10.2196/39504
Kiki Ferawati, Kongmeng Liew, Eiji Aramaki, Shoko Wakamiya
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引用次数: 0

摘要

背景:2021年是预防COVID-19疫苗接种的一年,这在普通人群中引发了更广泛的讨论,有些人赞成接种疫苗,有些人反对接种疫苗。受欢迎的社交媒体平台推特在提供有关COVID-19疫苗的信息方面发挥了重要作用,并有效地观察了公众的反应。我们关注的是来自日本和印度尼西亚的推文,这两个国家有大量的twitter用户,在这两个国家,对副作用的担忧一直被认为是疫苗犹豫的一个重要原因。目的:本研究旨在调查Twitter如何被用来报道疫苗相关的副作用,并比较辉瑞和Moderna在日本和印度尼西亚开发的两种信使RNA (mRNA)疫苗类型对这些副作用的提及。方法:从Twitter上获取2021年1月1日至2021年12月31日与COVID-19疫苗及其副作用相关的日语和印度尼西亚语关键词的推文数据。然后,我们删除了推文频率高的用户,并将多个用户的推文合并为一个句子,专注于用户层面的分析,结果是总共有214,165个用户(日本)和12,289个用户(印度尼西亚)。然后,我们对数据进行过滤,选择只提到辉瑞或Moderna的推文,并删除同时提到辉瑞和Moderna的推文。我们将副作用数与辉瑞和Moderna发布的公开报告进行了比较。之后,使用逻辑回归模型比较辉瑞和Moderna疫苗在每个国家的副作用。结果:我们观察到公开报道和推文的副作用比例有所不同。具体来说,“发烧”在推特上被提及的频率远高于公开报道的预期。我们还观察到来自日本和印度尼西亚的辉瑞疫苗和Moderna疫苗报道的副作用差异,日本推文报道的辉瑞疫苗副作用较多,印度尼西亚推文报道的Moderna疫苗副作用较多。结论:我们注意到Twitter上疫苗副作用监测和信息传播的可能后果,因为发烧似乎被过度代表。这可能是由于发热可能具有更高的严重性或可测量性,并讨论了进一步的影响。
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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Monitoring Mentions of COVID-19 Vaccine Side Effects on Japanese and Indonesian Twitter: Infodemiological Study.

Background: The year 2021 was marked by vaccinations against COVID-19, which spurred wider discussion among the general population, with some in favor and some against vaccination. Twitter, a popular social media platform, was instrumental in providing information about the COVID-19 vaccine and has been effective in observing public reactions. We focused on tweets from Japan and Indonesia, 2 countries with a large Twitter-using population, where concerns about side effects were consistently stated as a strong reason for vaccine hesitancy.

Objective: This study aimed to investigate how Twitter was used to report vaccine-related side effects and to compare the mentions of these side effects from 2 messenger RNA (mRNA) vaccine types developed by Pfizer and Moderna, in Japan and Indonesia.

Methods: We obtained tweet data from Twitter using Japanese and Indonesian keywords related to COVID-19 vaccines and their side effects from January 1, 2021, to December 31, 2021. We then removed users with a high frequency of tweets and merged the tweets from multiple users as a single sentence to focus on user-level analysis, resulting in a total of 214,165 users (Japan) and 12,289 users (Indonesia). Then, we filtered the data to select tweets mentioning Pfizer or Moderna only and removed tweets mentioning both. We compared the side effect counts to the public reports released by Pfizer and Moderna. Afterward, logistic regression models were used to compare the side effects for the Pfizer and Moderna vaccines for each country.

Results: We observed some differences in the ratio of side effects between the public reports and tweets. Specifically, fever was mentioned much more frequently in tweets than would be expected based on the public reports. We also observed differences in side effects reported between Pfizer and Moderna vaccines from Japan and Indonesia, with more side effects reported for the Pfizer vaccine in Japanese tweets and more side effects with the Moderna vaccine reported in Indonesian tweets.

Conclusions: We note the possible consequences of vaccine side effect surveillance on Twitter and information dissemination, in that fever appears to be over-represented. This could be due to fever possibly having a higher severity or measurability, and further implications are discussed.

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