Wakene Abdi D, Cooper Lauren N, Hanna John J, Perl Trish M, Lehmann Christoph U, Medford Richard J
Clinical Informatics Center, University of Texas Southwestern Medical Center, Dallas, TX, USA.
Division of Infectious Diseases and Geographic Medicine, Department of Internal Medicine, University of Texas Southwestern Medical Center, Dallas, TX, USA.
Antimicrob Steward Healthc Epidemiol. 2024 Sep 23;4(1):e141. doi: 10.1017/ash.2024.379. eCollection 2024.
Social media's arrival eased the sharing of mis- and disinformation. False information proved challenging throughout the coronavirus disease 2019 (COVID-19) pandemic with many clinicians and researchers analyzing the "infodemic." We systemically reviewed and synthesized COVID-19 mis- and disinformation literature, identifying the prevalence and content of false information and exploring mitigation and prevention strategies.
We identified and analyzed publications on COVID-19-related mis- and disinformation published from March 1, 2020, to December 31, 2022, in PubMed. We performed a manual topic review of the abstracts along with automated topic modeling to organize and compare the different themes. We also conducted sentiment (ranked -3 to +3) and emotion analysis (rated as predominately happy, sad, angry, surprised, or fearful) of the abstracts.
We reviewed 868 peer-reviewed scientific publications of which 639 (74%) had abstracts available for automatic topic modeling and sentiment analysis. More than a third of publications described mitigation and prevention-related issues. The mean sentiment score for the publications was 0.685, and 56% of studies had a negative sentiment (fear and sadness as the most common emotions).
Our comprehensive analysis reveals a significant proliferation of dis- and misinformation research during the COVID-19 pandemic. Our study illustrates the pivotal role of social media in amplifying false information. Research into the infodemic was characterized by negative sentiments. Combining manual and automated topic modeling provided a nuanced understanding of the complexities of COVID-19-related misinformation, highlighting themes such as the source and effect of misinformation, and strategies for mitigation and prevention.
社交媒体的出现使得错误信息和虚假信息的传播更加容易。在2019年冠状病毒病（COVID-19）大流行期间，虚假信息带来了诸多挑战，许多临床医生和研究人员对“信息疫情”进行了分析。我们系统地回顾并综合了关于COVID-19错误信息和虚假信息的文献，确定了虚假信息的流行程度和内容，并探索了缓解和预防策略。
我们在PubMed中识别并分析了2020年3月1日至2022年12月31日期间发表的与COVID-19相关错误信息和虚假信息的出版物。我们对摘要进行了人工主题审查，并结合自动主题建模来组织和比较不同的主题。我们还对摘要进行了情感（评分从-3到+3）和情绪分析（分为主要是高兴、悲伤、愤怒、惊讶或恐惧）。
我们回顾了868篇经过同行评审的科学出版物，其中639篇（74%）有可供自动主题建模和情感分析的摘要。超过三分之一的出版物描述了缓解和预防相关问题。这些出版物的平均情感得分为0.685，56%的研究有负面情绪（恐惧和悲伤是最常见的情绪）。
我们的综合分析显示，在COVID-19大流行期间，错误信息和虚假信息的研究大量增加。我们的研究说明了社交媒体在放大虚假信息方面的关键作用。对信息疫情的研究以负面情绪为特征。将人工和自动主题建模相结合，为理解COVID-相关错误信息的复杂性提供了细致入微的认识，突出了诸如错误信息来源和影响以及缓解和预防策略等主题。
