科学研究在 Twitter 上关于人类乳头瘤病毒疫苗讨论中的作用:社交网络分析

IF 3.5 Q1 HEALTH CARE SCIENCES & SERVICES
JMIR infodemiology Pub Date : 2024-05-09 DOI:10.2196/50551
Geneviève Jessiman-Perreault, Jean-Christophe Boucher, So Youn Kim, Nicole Frenette, Abbas Badami, Henry M Smith, Lisa K Allen Scott
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引用次数: 0

摘要

背景:人们对人类乳头瘤病毒(HPV)疫苗的态度以及在网络环境中分享的相关信息的准确性存在很大差异。在全球范围内实时接触有关 HPV 免疫接种的网络言论会影响人们对疫苗接种的态度,而错误信息的传播和对科学知识的歪曲则会导致人们对疫苗接种犹豫不决:在这项研究中,我们旨在更好地了解对疫苗持犹豫态度的群体和对疫苗持自信态度的群体在 Twitter(最近更名为 X)上分享的科学研究的类型和质量:为了分析科研成果在社交媒体上的使用情况,我们在 2019 年 1 月至 2021 年 5 月期间使用学术研究产品追踪应用编程接口,使用与 HPV 和 HPV 疫苗相关的关键词列表收集了推文和转发信息。从这组数据中,我们通过布尔搜索找出了提及或分享科学文献的推文,这些推文都包含嵌入式链接、标签或与科学论文相关的关键词。首先,我们使用社交网络分析来构建转发或回复网络,以识别属于疫苗自信群体或疫苗犹豫群体的用户集群。其次,我们根据证据类型对所有共享论文进行了主题评估。最后,我们比较了疫苗自信者社区和疫苗犹豫者社区中共享论文的研究证据质量和文献计量学:我们从大约 100 万条英语推文中提取了 250 篇独特的科学论文(包括同行评审论文、预印本和灰色文献)。结果:我们从大约 100 万条英语推文中提取了 250 篇独特的科学论文(包括同行评审论文、预印本和灰色文献),并生成了推特上分享科研成果的疫苗自信者和疫苗犹豫者社区的社交网络图。与疫苗自信群体分享的科学论文相比,疫苗犹豫群体分享的科学论文数量较少;然而,尽管这些论文发表在知名度较低的期刊上,其传播范围却更广:对疫苗持怀疑态度的群体采用了传统上由健康促进群体使用的传播工具。对疫苗有信心的群体将受益于更具凝聚力的传播策略,从而更广泛、更有效地传播他们的信息。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
The Role of Scientific Research in Human Papillomavirus Vaccine Discussions on Twitter: Social Network Analysis.

Background: Attitudes toward the human papillomavirus (HPV) vaccine and accuracy of information shared about this topic in web-based settings vary widely. As real-time, global exposure to web-based discourse about HPV immunization shapes the attitudes of people toward vaccination, the spread of misinformation and misrepresentation of scientific knowledge contribute to vaccine hesitancy.

Objective: In this study, we aimed to better understand the type and quality of scientific research shared on Twitter (recently rebranded as X) by vaccine-hesitant and vaccine-confident communities.

Methods: To analyze the use of scientific research on social media, we collected tweets and retweets using a list of keywords associated with HPV and HPV vaccines using the Academic Research Product Track application programming interface from January 2019 to May 2021. From this data set, we identified tweets referring to or sharing scientific literature through a Boolean search for any tweets with embedded links, hashtags, or keywords associated with scientific papers. First, we used social network analysis to build a retweet or reply network to identify the clusters of users belonging to either the vaccine-confident or vaccine-hesitant communities. Second, we thematically assessed all shared papers based on typology of evidence. Finally, we compared the quality of research evidence and bibliometrics between the shared papers in the vaccine-confident and vaccine-hesitant communities.

Results: We extracted 250 unique scientific papers (including peer-reviewed papers, preprints, and gray literature) from approximately 1 million English-language tweets. Social network maps were generated for the vaccine-confident and vaccine-hesitant communities sharing scientific research on Twitter. Vaccine-hesitant communities share fewer scientific papers; yet, these are more broadly disseminated despite being published in less prestigious journals compared to those shared by the vaccine-confident community.

Conclusions: Vaccine-hesitant communities have adopted communication tools traditionally wielded by health promotion communities. Vaccine-confident communities would benefit from a more cohesive communication strategy to communicate their messages more widely and effectively.

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