波兰语社交媒体中的 COVID-19 - 误传与政府

IF 3.4 3区 医学 Q1 HEALTH POLICY & SERVICES Health Policy and Technology Pub Date : 2024-05-15 DOI:10.1016/j.hlpt.2024.100871
Przemysław Waszak , Ewelina Łuszczak , Paweł Zagożdżon
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引用次数: 0

摘要

背景在 COVID-19 大流行期间,阴谋论和错误信息在社交媒体平台上激增。医学协会认识到这一问题的严重性,开始将其视为对公共卫生系统的重大威胁。本研究旨在量化波兰社交媒体上最常分享的 COVID-19 错误信息和政府官方信息的比例。使用 "COVID"、"koronawirus "或 "SARS-CoV-2 "等关键词对 2022 年 1 月 1 日至 6 月 30 日的波兰语社交媒体帖子进行了仔细研究。我们生成了一份包含分享、评论、点赞和反应(参与)的综合报告。我们分析了参与度最高的 40 个项目。为确保准确性,两位作者(均为医学博士)对每条信息进行了独立评估,以确定是否存在潜在的错误信息。结果我们确定了在社交媒体上分享的 161,404 条波兰语信息,代表了 41,432,352 次参与。排名前 40 位的项目(占所有项目的 0.02%)占参与次数(3,194,900 次)的 7.71%。被归类为错误信息的四个项目占前 40 个项目的 7.7%,累计参与次数达 244,700 次。所有被识别的项目都被标记为 "篡改新闻",因为它们依赖于未经核实或解释不当的数据;没有一个项目被归类为捏造新闻。在前 40 个项目中,政府来源占 4.1%,累计参与 130,800 次。应针对社交媒体平台和现实生活环境采取补救措施,以提高公众健康素养。
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COVID-19 in Polish-language social media - misinformation vs government information

Background

During the COVID-19 pandemic, a surge of conspiracy theories and misinformation proliferated across social media platforms. Recognizing the severity of the issue, medical associations began to regard it as a significant threat to public health systems. The objective of this study was to quantify the proportion of COVID-19 misinformation and official government information within the most frequently shared items on Polish social media.

Methods

The analysis utilized the BuzzSumo Enterprise Application. Polish-language social media posts from January 1 to June 30, 2022, were scrutinized using keywords such as "COVID," "koronawirus," or "SARS-CoV-2." A comprehensive report was generated, encompassing shares, comments, likes, and reactions (engagements). We analyzed the top 40 items that generated the most engagement. To ensure accuracy, two of the authors, both medical doctors, independently assessed each of them for potential misinformation.

Results

We identified 161,404 items in the Polish language that were shared on social media, representing 41,432,352 engagements. The top 40 items (0.02 % of all items) accounted for 7.71 % of engagements (3,194,900). Four items classified as misinformation accounted for 7.7 % of the Top 40 items, accumulating 244,700 engagements. All identified items were labeled as "manipulated news" due to their reliance on unverified or inappropriately interpreted data; none were classified as fabricated news. Government sources accounted for 4.1 % of the Top 40 items, accumulating 130,800 engagements.

Conclusions

This study highlights the significant prevalence of COVID-19 misinformation. Remedial measures should be implemented, addressing both social media platforms and real-life contexts, to enhance public health literacy.

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来源期刊
Health Policy and Technology
Health Policy and Technology Medicine-Health Policy
CiteScore
9.20
自引率
3.30%
发文量
78
审稿时长
88 days
期刊介绍: Health Policy and Technology (HPT), is the official journal of the Fellowship of Postgraduate Medicine (FPM), a cross-disciplinary journal, which focuses on past, present and future health policy and the role of technology in clinical and non-clinical national and international health environments. HPT provides a further excellent way for the FPM to continue to make important national and international contributions to development of policy and practice within medicine and related disciplines. The aim of HPT is to publish relevant, timely and accessible articles and commentaries to support policy-makers, health professionals, health technology providers, patient groups and academia interested in health policy and technology. Topics covered by HPT will include: - Health technology, including drug discovery, diagnostics, medicines, devices, therapeutic delivery and eHealth systems - Cross-national comparisons on health policy using evidence-based approaches - National studies on health policy to determine the outcomes of technology-driven initiatives - Cross-border eHealth including health tourism - The digital divide in mobility, access and affordability of healthcare - Health technology assessment (HTA) methods and tools for evaluating the effectiveness of clinical and non-clinical health technologies - Health and eHealth indicators and benchmarks (measure/metrics) for understanding the adoption and diffusion of health technologies - Health and eHealth models and frameworks to support policy-makers and other stakeholders in decision-making - Stakeholder engagement with health technologies (clinical and patient/citizen buy-in) - Regulation and health economics
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