Baydoun Atallah, Pereira Ian J, Turner Sandra, Siva Shankar, Albert Ashley A, Andrew Loblaw D, Simcock Richard A, Zaorsky Nicholas G, Katz Matthew S
Department of Radiation Oncology, University Hospitals of Cleveland, Cleveland, OH 44106, USA.
Queen's University, Kingston, ON K7L 3N6, Canada.
Clin Transl Radiat Oncol. 2022 Oct 25;39:100524. doi: 10.1016/j.ctro.2022.09.007. eCollection 2023 Mar.
For radiation oncology, social media is a favored communication platform, but it uses non-structured hashtags, which limits communication. In this work, we created a set of structured hashtags with key opinion leaders in radiation oncology, and we report on their use after two years post-deployment.
MATERIALS/METHODS: Hashtags were created, voted on, and refined by crowdsourcing 38 international experts, including physicians, physicists, patients, and organizations from North America, Europe, and Australia. The finalized hashtag set was shared with the radiation oncology community in September 2019. The number of tweets for each hashtag was quantified via Symplur through December 2021. For the top five tweeted hashtags, we captured the number of yearly tweets in the pre-deployment and post-deployment periods from 09/01/2019 to 08/31/2021.
The initial 2019 list contained 39 hashtags organized into nine categories. The top five hashtags by total number of tweets were: #Radonc, #PallOnc, #MedPhys, #SurvOnc, and #SuppOnc. Six hashtags had less than 10 total tweets and were eliminated. Post-deployment, there was an increase in the yearly tweets, with the following number of tweets by the second year post-deployment: #RadOnc (98,189 tweets), #MedPhys (15,858 tweets), and #SurvOnc (6,361 tweets). Two popular radiation oncology-related hashtags were added because of increased use: #DEIinRO (1,603 tweets by year 2) and #WomenWhoCurie (7,212 tweets by year 2). Over the two years, hashtags were used mostly by physicians (131,625 tweets, 34.8%).
We created and tracked structured social media hashtags in radiation oncology. These hashtags disseminate information among a diverse oncologic community. To maintain relevance, regular updates are needed.
对于放射肿瘤学而言，社交媒体是一个受欢迎的交流平台，但它使用的是非结构化标签，这限制了交流。在这项工作中，我们与放射肿瘤学领域的关键意见领袖共同创建了一组结构化标签，并报告了它们在部署两年后的使用情况。
材料/方法：通过众包方式让来自北美、欧洲和澳大利亚的38位国际专家（包括医生、物理学家、患者和组织）创建、投票并完善标签。最终确定的标签集于2019年9月与放射肿瘤学领域的社区分享。通过Symplur对每个标签的推文数量进行量化统计，截至2021年12月。对于推文数量排名前五的标签，我们统计了2019年9月1日至2021年8月31日部署前和部署后的年度推文数量。
2019年的初始列表包含39个标签，分为九个类别。按推文总数排名前五的标签分别是：#Radonc、#PallOnc、#MedPhys、#SurvOnc和#SuppOnc。有六个标签的推文总数少于10条，被剔除。部署后，年度推文数量有所增加，部署后第二年的推文数量如下：#RadOnc（98,189条推文）、#MedPhys（15,858条推文）和#SurvOnc（6,361条推文）。由于使用量增加，新增了两个与放射肿瘤学相关的热门标签：#DEIinRO（第二年1,603条推文）和#WomenWhoCurie（第二年7,212条推文）。在这两年中，使用标签的大多是医生（131,625条推文，占34.8%）。
我们在放射肿瘤学中创建并跟踪了结构化的社交媒体标签。这些标签在不同的肿瘤学社区中传播信息。为保持相关性，需要定期更新。
