新冠肺炎大流行期间社交媒体在健康虚假信息和虚假信息中的作用:文献计量分析。

IF 3.5 Q1 HEALTH CARE SCIENCES & SERVICES JMIR infodemiology Pub Date : 2023-09-20 DOI:10.2196/48620
Funmi Adebesin, Hanlie Smuts, Tendani Mawela, George Maramba, Marie Hattingh
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引用次数: 0

摘要

背景:利用社交媒体平台获取信息的情况持续增加。社交媒体平台可以用来即时向世界各地的人们传播重要信息。然而,它们的病毒性也使得分享错误信息、虚假信息、未经核实的信息和假新闻变得容易。在新冠肺炎大流行期间,对社交媒体平台寻求信息的空前依赖伴随着错误信息和虚假信息事件的增加。因此,在新冠肺炎疫情最严重的时候,与社交媒体在传播健康错误信息和虚假信息方面的作用有关的科学出版物数量有所增加。健康方面的错误信息和虚假信息,尤其是在全球公共卫生灾难时期,往好了说可能会导致对政策制定者的信任受到侵蚀,往坏了说可能导致致命后果。目的:本文报告了一项文献计量分析,旨在调查自新冠肺炎大流行开始以来,与社交媒体作为健康错误信息和虚假信息驱动因素的作用相关的研究出版物的演变。此外,本研究旨在确定与当前研究相关的热门关键词、利基话题、作者和出版商,以及自新冠肺炎大流行开始以来,作者之间在与社交媒体在健康错误信息和虚假信息中的作用相关的话题上的全球合作。方法:Scopus数据库于2023年6月8日访问,使用医学主题标题和作者定义的术语组合创建以下搜索短语,以及关键字字段:(“健康*”或“医疗”)与(“错误信息”或“虚假信息”或”假新闻“)与(”社交媒体“或”推特“或”脸书“或”YouTube“或”WhatsApp“或”Instagram“或”TikTok“)与。使用Microsoft Excel(微软公司)、VOSviewer(莱顿大学科学与技术研究中心)和RStudio(Posit,PBC)Bibliometrix(K-Synth Srl)中的Bibliobshing包,对2020年至2023年6月期间发表的943篇研究论文进行了分析。结果:2022年发表的论文数量最多(387/943,41%)。大多数出版物(725/943,76.9%)是文章。JMIR发表的研究论文最多(54/943,5.7%)。来自美国的作者合作最多,有311篇合著研究论文。关键字“新冠肺炎”、“社交媒体”和“错误信息”是前三大热门关键字,而“学习系统”、“学习模型”和“学习算法”被揭示为新冠肺炎疫情期间社交媒体在健康错误信息和虚假信息中的作用的小众主题。结论:作者之间的合作可以提高他们的生产力和引用次数。研究人员可以在未来的研究中利用“学习系统”、“学习模型”和“学习算法”等利基话题,分析社交媒体对全球公共卫生紧急情况期间健康错误信息和虚假信息的影响。
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The Role of Social Media in Health Misinformation and Disinformation During the COVID-19 Pandemic: Bibliometric Analysis.

Background: The use of social media platforms to seek information continues to increase. Social media platforms can be used to disseminate important information to people worldwide instantaneously. However, their viral nature also makes it easy to share misinformation, disinformation, unverified information, and fake news. The unprecedented reliance on social media platforms to seek information during the COVID-19 pandemic was accompanied by increased incidents of misinformation and disinformation. Consequently, there was an increase in the number of scientific publications related to the role of social media in disseminating health misinformation and disinformation at the height of the COVID-19 pandemic. Health misinformation and disinformation, especially in periods of global public health disasters, can lead to the erosion of trust in policy makers at best and fatal consequences at worst.

Objective: This paper reports a bibliometric analysis aimed at investigating the evolution of research publications related to the role of social media as a driver of health misinformation and disinformation since the start of the COVID-19 pandemic. Additionally, this study aimed to identify the top trending keywords, niche topics, authors, and publishers for publishing papers related to the current research, as well as the global collaboration between authors on topics related to the role of social media in health misinformation and disinformation since the start of the COVID-19 pandemic.

Methods: The Scopus database was accessed on June 8, 2023, using a combination of Medical Subject Heading and author-defined terms to create the following search phrases that targeted the title, abstract, and keyword fields: ("Health*" OR "Medical") AND ("Misinformation" OR "Disinformation" OR "Fake News") AND ("Social media" OR "Twitter" OR "Facebook" OR "YouTube" OR "WhatsApp" OR "Instagram" OR "TikTok") AND ("Pandemic*" OR "Corona*" OR "Covid*"). A total of 943 research papers published between 2020 and June 2023 were analyzed using Microsoft Excel (Microsoft Corporation), VOSviewer (Centre for Science and Technology Studies, Leiden University), and the Biblioshiny package in Bibliometrix (K-Synth Srl) for RStudio (Posit, PBC).

Results: The highest number of publications was from 2022 (387/943, 41%). Most publications (725/943, 76.9%) were articles. JMIR published the most research papers (54/943, 5.7%). Authors from the United States collaborated the most, with 311 coauthored research papers. The keywords "Covid-19," "social media," and "misinformation" were the top 3 trending keywords, whereas "learning systems," "learning models," and "learning algorithms" were revealed as the niche topics on the role of social media in health misinformation and disinformation during the COVID-19 outbreak.

Conclusions: Collaborations between authors can increase their productivity and citation counts. Niche topics such as "learning systems," "learning models," and "learning algorithms" could be exploited by researchers in future studies to analyze the influence of social media on health misinformation and disinformation during periods of global public health emergencies.

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