“MedEd” on Twitter: A Social Network Analysis

IF 0.3 Q3 MEDICINE, GENERAL & INTERNAL
Shazia Iqbal, Shahzad Ahmad, M. Samsudin, Saood Khan Lodhi, Salima Naveed Manji
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Abstract

Background. In the current era, Twitter is an increasingly popular tool for the dissemination of information as a social media voice. Social media is a valid, but underutilized, education tool at medical education institutions. Social media technologies provide opportunities for the presentation of information in alternative and multiple formats to enhance engagement, content creation, and motivation for individual and collaborative learning. Objective. This study examined the type of social structure and sub-clusters do exist regarding “MedEd” on the Twitter network. Additionally, it determined the top opinion leaders in these networks and which type of topics generates users’ interest regarding “MedEd”. Methods. This study applied NodeXL to analyze the results and retrieved Twitter data on November 1, 2022 by using the keywords “MedEd”. The data were saved and interpreted in the “vertices” and “edges” on the NodeXL worksheets. Results. We found that the top opinion leader (vertex) “Cryptovitas” had the highest in- betweenness and out-degree centrality. “Innov_medicine” had the in-degree centrality for networks. “In-Degree” and “Out-Degree” are the count of Tweets an opinion leader gets and forwards messages out, correspondingly. The study found that although “Cryptovitas” had the highest in-betweenness centrality, “taylorswift13” had the maximum number of followers (91,523,045) with in-betweenness centrality of 0.0. This indicates that the vertex having maximum influence with the largest number of in-betweenness centrality has not linked with several followers. Conclusions. Using Twitter embodies a potential prospect to engage the medical education community. The content of top networks’ tweets was around the number of “MedEd” innovations with the potential to significantly improve medical education delivery and innovative technologies in healthcare services. There is no link between the number of followers and in-betweenness centrality to influence the strength of social media voice. Although clinical and social tweets were there, not much was discussed regarding the curriculum reforms, continued professional development, technical issues in MedEd, and assessments. This triggers the insistence for rapid and innovative adaptations to the new learning environments and remarkable revolutions in medical education, including the encouragement of evidence-based education. The Twitter discussions promoted a research network circulating a wide range of informative innovations and collaborations.
Twitter上的“MedEd”:一个社会网络分析
背景。在当今时代,Twitter作为一种社交媒体的声音,是一种越来越受欢迎的信息传播工具。在医学教育机构中,社交媒体是一种有效但未被充分利用的教育工具。社交媒体技术为以多种形式呈现信息提供了机会,以增强参与度、内容创作以及个人和协作学习的动机。目标。本研究考察了Twitter网络中“MedEd”存在的社会结构类型和子集群。此外,它还确定了这些网络中的顶级意见领袖,以及哪种类型的话题会引起用户对“MedEd”的兴趣。方法。本研究采用NodeXL对结果进行分析,并以关键词“MedEd”检索2022年11月1日的Twitter数据。数据在NodeXL工作表的“顶点”和“边”中保存和解释。结果。结果表明,最高意见领袖(顶点)“隐vitas”具有最高的中间度和外度中心性。“Innov_medicine”具有网络的度中心性。“In-Degree”和“out - degree”是意见领袖获得和转发消息的数量。研究发现,虽然“Cryptovitas”的中间中心性最高,但“taylorswift13”的中间中心性为0.0,粉丝人数最多(91523045人)。这表明具有最大影响且中间中心性数量最多的顶点没有与多个follower相关联。结论。使用Twitter体现了与医学教育界接触的潜在前景。顶级网络推文的内容围绕着“MedEd”创新的数量,这些创新有可能显著改善医疗教育的提供和医疗服务中的创新技术。关注者的数量和中间性中心性对社交媒体声音强度的影响之间没有联系。尽管有临床和社会方面的推文,但关于课程改革、持续的专业发展、MedEd的技术问题和评估方面的讨论并不多。这促使人们坚持快速和创新地适应新的学习环境,并在医学教育方面进行重大变革,包括鼓励循证教育。Twitter上的讨论促进了一个研究网络的形成,这个网络传播着广泛的信息创新与合作。
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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