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Development and dissemination of structured hashtags for radiation oncology: Two-Year trends

  • Atallah Baydoun
    Affiliations
    Department of Radiation Oncology, University Hospitals of Cleveland, Cleveland, OH 44106, USA
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  • Ian J. Pereira
    Affiliations
    Queen’s University, Kingston, ON K7L 3N6, Canada
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  • Sandra Turner
    Affiliations
    Crown Princess Mary Cancer Centre, Westmead 2145, Australia
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  • Shankar Siva
    Affiliations
    University of Melbourne, Melbourne 3010, Australia
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  • Ashley A. Albert
    Affiliations
    Arizona Center for Cancer Care, Scottsdale, AZ 85258, USA
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  • D. Andrew Loblaw
    Affiliations
    Department of Radiation Oncology, Sunnybrook Odette Cancer Centre, University of Toronto, Toronto, ON M4N 3M5, Canada
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  • Richard A. Simcock
    Affiliations
    Brighton and Sussex University Hospitals NHS Trust, Brighton BN2 1DH, UK
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  • Author Footnotes
    1 Both Authors contributed equally to the redaction of this manuscript.
    Nicholas G. Zaorsky
    Correspondence
    Corresponding authors at: Department of Radiation Oncology, UH Cleveland Medical Center, Seidman Cancer Center, 11100 Euclid Avenue, Cleveland, OH 44106, USA (N.G. Zaorsky). Department of Radiation Oncology, The Cancer Center at Lowell General Hospital, 295 Varnum Avenue, Lowell, MA 01854, USA (M. Katz).
    Footnotes
    1 Both Authors contributed equally to the redaction of this manuscript.
    Affiliations
    Department of Radiation Oncology, University Hospitals of Cleveland, Cleveland, OH 44106, USA

    School of Medicine, Case Western Reserve University, Cleveland, OH 44106, USA
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  • Author Footnotes
    1 Both Authors contributed equally to the redaction of this manuscript.
    Matthew S. Katz
    Correspondence
    Corresponding authors at: Department of Radiation Oncology, UH Cleveland Medical Center, Seidman Cancer Center, 11100 Euclid Avenue, Cleveland, OH 44106, USA (N.G. Zaorsky). Department of Radiation Oncology, The Cancer Center at Lowell General Hospital, 295 Varnum Avenue, Lowell, MA 01854, USA (M. Katz).
    Footnotes
    1 Both Authors contributed equally to the redaction of this manuscript.
    Affiliations
    Radiation Oncology Associates, PA, Lowell, MA 01854, USA
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  • Author Footnotes
    1 Both Authors contributed equally to the redaction of this manuscript.
Open AccessPublished:October 25, 2022DOI:https://doi.org/10.1016/j.ctro.2022.09.007

      Abstract

      Purpose

      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.

      Results

      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%).

      Conclusion

      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.

      Keywords

      1. Introduction

      Since the 2000s, advances in digital technologies have transformed the human communicative process into its current form of predominant virtual interaction [
      • Kostkova P.
      Grand challenges in digital health.
      ,
      • Hesse B.W.
      • Moser R.P.
      • Rutten L.J.
      Surveys of physicians and electronic health information.
      ]. This transformation was displayed in multiple professional medical communities [
      • Bibault J.-E.
      • Katz M.S.
      • Motwani S.
      Social media for radiation oncologists: a practical primer.
      ,
      • Kutikov A.
      • Woo H.H.
      • Catto J.W.
      Urology tag ontology project: standardizing social media communication descriptors.
      ,
      • Attai D.J.
      • Cowher M.S.
      • Al-Hamadani M.
      • Schoger J.M.
      • Staley A.C.
      • Landercasper J.
      Twitter social media is an effective tool for breast cancer patient education and support: patient-reported outcomes by survey.
      ], that adapted to this new environment by curating health information using specialty-specific structured hashtags, e.g. in urology [
      • Kutikov A.
      • Woo H.H.
      • Catto J.W.
      Urology tag ontology project: standardizing social media communication descriptors.
      ]. Hashtags are created by placing the hash character # before a word or unspaced phrase [
      • Zadeh L.A.
      • Abbasov A.M.
      • Shahbazova S.N.
      Analysis of Twitter hashtags: Fuzzy clustering approach.
      ]. While the primary function of hashtags is to serve as an information label, analysis of their use pattern can inform about users’ attitude towards a subject, as well as temporal and locational aspects of events or debates [
      • Laucuka A.
      Communicative functions of hashtags.
      ], including health-related topics [
      • Xu W.W.
      • Chiu I.-H.
      • Chen Y.
      • Mukherjee T.
      Twitter hashtags for health: applying network and content analyses to understand the health knowledge sharing in a Twitter-based community of practice.
      ].
      For radiation oncology, Twitter has been a favored communication platform to disseminate specialty-related research and educational resources [
      • Rahimy E.
      • Sandhu N.K.
      • Giao D.M.
      • Pollom E.L.
      # TrendingNow: instagram versus twitter activity among radiation oncology patients and professionals.
      ]. Despite the presence of cancer-specific [
      • Katz M.S.
      • Utengen A.
      • Anderson P.F.
      • Thompson M.A.
      • Attai D.J.
      • Johnston C.
      • et al.
      Disease-specific hashtags for online communication about cancer care.
      ] and oncology-specific hashtags list since 2016 [
      • Pemmaraju N.
      • Thompson M.A.
      • Qazilbash M.
      Disease-specific hashtags and the creation of Twitter medical communities in hematology and oncology.
      ], conversation in the radiation oncology community mostly took place through random non-structured hashtags or without hashtags, which limited its visibility and influence. Therefore, in September 2019, our group began the development the first structured set of radiation oncology hashtags for organized social media use [
      • Pereira I.
      • Turner S.
      • Siva S.
      • Albert A.A.
      • Loblaw D.A.
      • Simcock R.A.
      • et al.
      Development of Structured Radiation Oncology Hashtags to Improve Online Communication.
      ]. Since then, the use of these hashtags on Twitter has been tracked but has never been analyzed.
      In this article, we aim to describe the development of these hashtags and to analyze the pattern of structured hashtag use over the two years after its development. In order to assess the set value and guide future modifications, we partition our analysis through before and after deployment in 2019. The results of this article would be useful to help improve social media communication in radiation oncology. The hashtags are relevant to physicians, other healthcare workers, organizations, patients, and media.

      2. Methods

      2.1 Establishment of the structured hashtags set

      In order to establish a radiation oncology-related set, we first evaluated structured hashtag models for oncology [
      • Pemmaraju N.
      • Thompson M.A.
      • Qazilbash M.
      Disease-specific hashtags and the creation of Twitter medical communities in hematology and oncology.
      ], pathology [
      • Isom J.
      • Walsh M.
      • Gardner J.M.
      Social media and pathology: where are we now and why does it matter?.
      ], radiology [
      • Hawkins C.M.
      Radiology’s social media hashtag ontology: codifying online data.
      ], and urology [
      • Kutikov A.
      • Woo H.H.
      • Catto J.W.
      Urology tag ontology project: standardizing social media communication descriptors.
      ] already published on Symplur™ [

      Symplur LLC. Symplur: Healthcare analytics products for social and real-world data. http://www.symplur.com December 4, 2021.

      ], a data analytics website which aggregates and monitors hashtag use on Twitter. In addition, we also gathered the commonly used hashtags in the radiation oncology Twitter communication.
      Second, we evaluated the initially collected hashtags and we prioritized the collection by relevance and frequency. Afterwards, we emailed the refined list to 38 key opinion leaders from professional societies and academic journals across North America, Europe, and Australia to further refine the collection. The reviewers included 10 leaders in the field of radiation oncology (eight radiation oncologists, one trainee, and one radiation therapist) from across North America. The remaining reviewers were experts from professional societies and academic journals across North America, Europe, and Australia. For similar or closely related hashtags, we crowdsourced preferred terminology through anonymous surveys delivered to the radiation oncology community using Twitter or SurveyMonkey. The surveys were performed separately for each hashtag between June – July 2018. In each survey, voter had the option to vote for a preferred hashtag from a list of three to five chosen hashtags or suggest a new hashtag. Furthermore, we also engaged the Society for Women in Radiation Oncology (SWRO) at the time of generating the original hashtag set to conduct an internal poll comparing preferred hashtags to include for women in radiation oncology. When possible, we also cross-referenced duplicate hashtags relevant to radiation oncology with actively used hashtags from other cancer-specific [
      • Katz M.S.
      • Utengen A.
      • Anderson P.F.
      • Thompson M.A.
      • Attai D.J.
      • Johnston C.
      • et al.
      Disease-specific hashtags for online communication about cancer care.
      ] or oncology-specific structured lists [
      • Pemmaraju N.
      • Thompson M.A.
      • Qazilbash M.
      Disease-specific hashtags and the creation of Twitter medical communities in hematology and oncology.
      ].
      The finalized radiation oncology structured hashtags set was submitted in March 2019 to the analytics software and shared with the radiation oncology community formally in September 2019 when presented at the ASTRO annual meeting [
      • Pereira I.
      • Turner S.
      • Siva S.
      • Albert A.A.
      • Loblaw D.A.
      • Simcock R.A.
      • et al.
      Development of Structured Radiation Oncology Hashtags to Improve Online Communication.
      ].

      2.2 Set tracking, analysis, and update

      Through the software, we accessed each hashtag to quantify the total number of tweets and the mean number of tweets per day for the period extending from the inception date of each hashtag until the analysis date on 12/21/2021. For the top five tweeted hashtags, we captured more detail on the number of yearly tweets, users, and percentage growth in the pre-deployment (September 1, 2017–August 31, 2019) and post-deployment (September 1, 2019–August 31, 2021) periods. Moreover, the tweets stakeholder groups for the top five and newly incorporated tweets were captured, and the number of tweets for each group was reported.
      Finally, new radiation oncology-related hashtags were evaluated for possible incorporation in the hashtags set. In 2021, we observed an increasing use of two hashtags: #WomenWhoCurie for women in radiation oncology and #DEIinRO for overall diversity in the field. We therefore conducted a similar more detailed analysis of these two hashtags and the two initially designed for similar use, #RadOncWomen and #RODiversity respectively.

      3. Results

      3.1 Establishment of the structured hashtags set

      The workflow for the set establishment is featured in Fig. 1. The initial collection contained 63 hashtags then five were subsequently excluded. The 58 remaining hashtags were shared with 38 reviewers as detailed in the methods. Two concepts, medical physics and radiation drug interactions, had competing hashtags that were resolved through separate surveys that did not include the 38 initial reviewers. For radiation drug interactions #RTdrugcombo was preferred (60 %) among 33 SurveyMonkey participants, and for medical physics #MedPhys was preferred (57 %) among 28 participants over a Twitter poll. The SWRO poll included 53 respondents, and #RadOncWomen was the most supported hashtag (49 %) for inclusion and was then included in the original set.
      Figure thumbnail gr1
      Fig. 1Workflow for establishment, tracking, and update of the structured hashtags set.
      The initial list contained 39 hashtags organized into nine categories as listed in Table 1. The set was shared with the radiation oncology community during the 61st annual meeting of the American Society of Radiation Oncology (ASTRO) meeting in September 2019 [
      • Pereira I.
      • Turner S.
      • Siva S.
      • Albert A.A.
      • Loblaw D.A.
      • Simcock R.A.
      • et al.
      Development of Structured Radiation Oncology Hashtags to Improve Online Communication.
      ].
      Table 1Initial list of radiation oncology hashtag collection and the subsequent edits.
      Hashtags from the initial list that were dropped-out are highlighted with double strikethrough. Hashtags from the initial list that were replaced are highlighted with single strikethrough. Replacement hashtags are highlighted in bold.

      3.2 Set tracking and analysis

      Fig. 2 displays the bar charts for the number of total tweets since start date and the number of tweets per day. The number of total tweets is also displayed in Table 1. The top five hashtags by the total number of tweets were respectively: #Radonc, #PallOnc, #MedPhys, #SurvOnc, and #SuppOnc. When accounting for the number of tweets per day, the top five hashtags were respectively: #Radonc, #PallOnc, #MedPhy, #SBRT, and #SurvOnc. Six hashtags had less than 10 total tweets from start date till 12/21/2021: #RadNTT (1 tweet), #OrganPres (1 tweet), #MedDosim (1 tweet), #CaHypox (3 tweets), #RTSim (5 tweets), and #StereoRT (8 tweets). Despite that the topics of diversity and inclusion in radiation oncology and women in radiation oncology had gained a significant amount of attention in the radiation oncology community since 2019, #RadOncWomen and #RadOncDiversity exhibited only 5.30 and 0.09 tweets per day respectively. In parallel, our group observed an increasing use of the respectively competing hashtags #WomenWhoCurie, #RadOncWomen, and #DEIinRO.
      Figure thumbnail gr2
      Fig. 2Hashtags tracking results: Number of total tweets and tweets per day for each hashtag since its start date.
      The tracking period included one year (September 1, 2018 - August 31, 2019) pre-deployment of the hashtags set, and two consecutive years (September 1, 2019 - August 31, 2020 and September 1, 2020 - August 31, 2021) post-deployment. A surge in the yearly tweets occurred after September 2019 for each of the top five hashtags except #PallOnc. #RadOnc increased from 76,970 pre-deployment to 105,468, and 98,189 first- and second-year post-deployment, respectively. #MedPhys increased from 76,970 pre-deployment to 105,468, and 98,189 first- and second-year post-deployment, respectively. #SurvOnc increased from 865 pre-deployment to 5,779, and 6,361 first- and second-year post-deployment, respectively. #SuppOnc increased from 3,864 pre-deployment to 4,520, and 8,497 first- and second-year post-deployment, respectively. #PallOnc decreased from 12,318 pre-deployment to 10,285, and 6,361 first- and second-year post-deployment, respectively. The number of tweets per month for the period extending from September 2019 till August 2020 is provided in Supplementary material. Among the top five tweets, #RadOnc had a surge of 10,978 tweets during September 2019 that is likely related to the meeting-related tweets, but the number of tweets throughout the whole year was overall steady. The growth rate over the tracking periods is displayed in Table 2 for the number of tweets and in Table 3 for the number of users. #PallOnc had a consistently negative growth rate, though the number of yearly tweets remained relatively high. For the number of tweets, #SurvOnc had its peak growth rate during the first-year post-deployment, while #Supponc had its peak growth rate during the second-year post-deployment. #RadOnc and #MedPhys had their peak in the pre-deployment year and a similar trend was observed for the growth in the number of users.
      Table 2Number of tweets and percentage growth over the tracking period for the top five hashtags.
      Period 2Period 3Period 4
      Nb. Tweets% GrowthNb. Tweets% GrowthNb. Tweets% Growth
      #RadOnc76,97099.69 %105,46837.02 %98,189−6.90 %
      #PallOnc12,318−18.42 %10,285−16.50 %6361−38.15 %
      #MedPhys316045042.86 %12,200286.08 %15,85829.98 %
      #SurvOnc865−17.46 %5779568.09 %13,043125.70 %
      #SuppOnc386436.10 %452016.98 %849787.99 %
      (Period 2: 09/01/2018 – 08/31/2019, Period 3: 09/01/2019 – 08/31/2020, Period 4: 09/01/2020 – 08/31/2021. Nb. Tweets = Number of Tweets. %Growth = percentage growth calculated as = 100 * (Nb Tweets of current period – Nb. Tweets of previous period) / Nb. Tweets of previous period).
      Table 3Number of tweets and percentage growth over the tracking period for the top five hashtags.
      Period 2Period 3
      Nb. Users% GrowthNb. Users% Growth
      #RadOnc784257.19 %978624.79 %
      #PallOnc2701−18.14 %2435−9.85 %
      #MedPhys104914885.71 %2396128.41 %
      #SurvOnc468−1.71 %1435206.62 %
      #SuppOnc94014.77 %106313.09 %
      (Period 2: 09/01/2018 – 08/31/2019, Period 4: 09/01/2019 – 08/31/2020. Nb. Users = Number of users. %Growth = percentage growth calculated as = 100 * (Nb Users of current period – Nb. Users of previous period) / Nb. Users of previous period).
      Fig. 3 displays the number of tweets over each period for #RadOncDiversity versus #DEIinRo (Fig. 3A), and #RadOncWomen versus #WomenWhoCurie. When compared head-to-head, #DEIinRO displayed a relatively high number of tweets (n = 1,340) in the third period compared to #RadOncDiversity (n = 6). Similarly, the number of tweets for the last two periods were significantly higher for #WomenWhoCurie (n = 7,272 and n = 6,185, respectively) compared to #RadOncWomen (n = 1,972 and n = 1,009).
      Figure thumbnail gr3
      Fig. 3Number of total tweets one-year pre-deployment of the hashtags set (September 1, 2018 - August 31, 2019), year one post-deployment (September 1, 2019 - August 31, 2020), and year two (September 1, 2020- August 31, 2021) post-deployment for: #RadOncDiversity vs #DEIinRO (a), #RadOncWomen vs WomenWhoCurie (b), and stakeholders patient advocate vs Journalist/Media (c).
      The numbers of tweets stratified per stakeholder category for the top five hashtags and for #RadOncDiversity, #DEIinRO, #RadOncWomen, and #WomenWhoCurie are provided in the supplementary material. As expected, the number of tweets for almost all the hashtags demonstrated a clear increase after September 2019 through August 2021. For each of the nine hashtags the top users were identified as being physicians with a total of 131,625 tweets accounting for 34.8 %. It is also useful to note that hashtags were used among non-physician stakeholders categories such as patient advocate (total of 5628 tweets accounting for 1.5 %), and journalist/media (total of 2,601 tweets accounting for 0.7 %). The increased use of the structured hashtags also extended to the non-health care providers category. For example, there was more than 60 % increase in the number of tweets related to the top five hashtags in the patient advocate and journalist/media stakeholder categories as featured in Fig. 3C. Finally, the growing use of these hashtags is also reflected by inter-user exchange, where post-deployment #RadOnc network analysis for example shows denser connections as displayed in Fig. 4.
      Figure thumbnail gr4
      Fig. 4#RadOnc network analysis two-year (September 1, 2018 - August 31, 2019) pre-deployment (a) and two-year (September 1, 2019 - August 31, 2021) post-deployment (b). Larger size nodes and thicker lines indicate more interaction and stronger connection. Different node colors refer to different stakeholders: doctors in light blue, advocacy organization in light green, investigator in dark green, research in purple, and governmental organization in pink. (For interpretation of the references to colour in this figure legend, the reader is referred to the web version of this article.)

      3.3 Set update

      Given the tracking analysis, the set of radiation oncology hashtags was adjusted so that the six hashtags appearing in less than 10 tweets were removed. The topics of women in radiation oncology and diversity and inclusion in radiation oncology will now be tagged through #WomenWhoCurie and #DEIinRO. The finalized set of 33 hashtags is summarized in supplementary Table 1 and will be disseminated again with the radiation oncology community in the 64th annual ASTRO meeting in 2022.

      4. Discussion

      The use of internet for retrieval of medical knowledge has increased among health care consumers from 25 % in 2000 to 61 % in 2008 [
      • Hesse B.W.
      • Moser R.P.
      • Rutten L.J.
      Surveys of physicians and electronic health information.
      ] and social media networks like Twitter are a major channel for health communication among health practitioners [
      • Novak J.
      • Cui Y.
      • Frankel P.
      • Sedrak M.S.
      • Glaser S.
      • Li R.
      • et al.
      Growth of the social# RadOnc network on twitter.
      ,
      • Markham M.J.
      • Gentile D.
      • Graham D.L.
      Social media for networking, professional development, and patient engagement.
      ]. Under this perspective, we started this initiative of configuring the communication descriptors among radiation oncology providers and consumers, aiming for two goals: 1) amplify the communication between practitioners and 2) assist patients in identifying reliable information that can empower their decision making. The ASTRO meeting program is usually available online by September. In order to have a reasonable demarcation of the pre- and post-deployment era we choose September 1, 2019 as the beginning of post-deployment tracking. Preliminary results from the two-years tracking in this manuscript indicate that the selected hashtags have gained considerable popularity among the different stakeholders, including radiation oncology community and patients. The decrease in the number of yearly tweets for #PallOnc might be related to the presence of other three other competing hashtags (#PalliativeCare, #HPM, and #HAPC) that had an increase in the yearly tweets within the tracking periods (Supplementary Table 5). The peak growth for #RadOnc and #MedPhys has occurred in the pre-deployment area, and this is likely related to a number of factors, including the fact that the inception date of #MedPhys falls within this tracking period, and the inherent popularity of these two main hashtags within the radiation oncology community.
      The presented tracking reflects a significant increase in the hashtags used among different stakeholders’ categories. In parallel to the hashtags of urologic oncology [
      • Borgmann H.
      • Loeb S.
      • Salem J.
      • Thomas C.
      • Haferkamp A.
      • Murphy D.G.
      • et al.
      Activity, content, contributors, and influencers of the twitter discussion on urologic oncology.
      ], most of the radiation oncology stakeholders belong to the health care community. For urologic oncology, the top stakeholders belonged to health organization [
      • Borgmann H.
      • Loeb S.
      • Salem J.
      • Thomas C.
      • Haferkamp A.
      • Murphy D.G.
      • et al.
      Activity, content, contributors, and influencers of the twitter discussion on urologic oncology.
      ], but in radiation oncology physicians were the top stakeholder. In addition, the hashtag set also gained popularity among other categories such as governmental organizations and non-health care related individuals. Such finding reinforces the concept of virtual community of practice previously introduced by Xu et al. [
      • Xu W.W.
      • Chiu I.-H.
      • Chen Y.
      • Mukherjee T.
      Twitter hashtags for health: applying network and content analyses to understand the health knowledge sharing in a Twitter-based community of practice.
      ]. Under this concept, the community of practice, despite having different but complementary motivation for a health-related topic, shares the same interest domain on Twitter, and uses the hashtags as an authentic source for knowledge diffusion [
      • Xu W.W.
      • Chiu I.-H.
      • Chen Y.
      • Mukherjee T.
      Twitter hashtags for health: applying network and content analyses to understand the health knowledge sharing in a Twitter-based community of practice.
      ]. While the actual interactions are far more complicated, Fig. 4 displays a snapshot illustration of the set community of practice, and the data provided for stakeholders in the supplementary Table 2 and Table 3 provide a quantitative insight about this community.
      Pertinent to the health care practitioners and radiation oncology researchers, the use of the hashtag set is likely to thrive further with the recent trend of using tweetorials for research result dissemination [
      • Breu A.C.
      From tweetstorm to tweetorials: threaded tweets as a tool for medical education and knowledge dissemination.
      ] or arranging a Twitter-based journal club [
      • Topf J.M.
      • Sparks M.A.
      • Phelan P.J.
      • Shah N.
      • Lerma E.V.
      • Graham-Brown M.P.M.
      • et al.
      The evolution of the journal club: from Osler to Twitter.
      ]. A tweetorial is a neologism combining tweet and tutorial defined as a series of sequential threaded tweets employed to overcome the character limit of a single tweet [
      • Breu A.C.
      Why is a cow? Curiosity, tweetorials, and the return to why.
      ]. Tweetorials use for medical education has flourished recently [
      • Breu A.C.
      • Abrams H.R.
      • Manning K.D.
      • Cooper A.Z.
      Tweetorials for Medical Educators.
      ], especially when used for dissemination of scholarly information such as new research findings [
      • Chary M.A.
      • Chai P.R.
      disseminating information, and sparking further scientific discussion with social media.
      ]. Since there is no feature in Twitter that enables tweetorial-specific hashtags, the hashtag set can be used in tweetorial as an instant information vector for research, providing a wide forum of discussion among peers and residents. In parallel, the hashtags can be used in the announcement process of the Twitter-based journal club, and this has been already in practice via the use of #RadOnc [
      • Prabhu A.V.
      • Beriwal S.
      • Ayyaswami V.
      • Simcock R.A.
      • Katz M.S.
      # RadOnc: characterization of the worldwide radiation oncology Twitter network.
      ].
      Given Twitter’s interactive nature, any structured hashtag set is likely to need a regular update that would be influenced by contemporary social trends and concerns [
      • Katz M.S.
      • Anderson P.F.
      • Thompson M.A.
      • Salmi L.
      • Freeman-Daily J.
      • Utengen A.
      • et al.
      Organizing online health content: developing hashtag collections for healthier internet-based people and communities.
      ]. Usually, simply stated, short hashtags and those with abbreviated terminologies such as #RadOnc are practical to use. Nonetheless, it seems that also hashtags relating to a historical figure or commonly used slogan, and those promoted by influential organizations would be rather attractive to the twitter community. For example, #WomenWhoCurie was first used on November 7, 2018 at the 151st birthday of Marie Curie as part of raising awareness for gender inequity in radiation oncology [
      • Albert A.A.
      • Knoll M.A.
      • Doke K.
      • Masters A.
      • Lee A.
      • Dover L.
      • et al.
      # WomenWhoCurie: leveraging social media to promote women in radiation oncology.
      ], and it was simultaneously promoted afterwards by ASTRO, SWRO, and Radiation Oncology Women’s Facebook group [
      • Albert A.A.
      • Knoll M.A.
      • Doke K.
      • Masters A.
      • Lee A.
      • Dover L.
      • et al.
      # WomenWhoCurie: leveraging social media to promote women in radiation oncology.
      ]. Similarly, #DEIinRO gained its popularity after being adapted by ASTRO’s Committee on Health Equity, Diversity, and Inclusion and marketed as a slogan for its social education series [
      • Suneja G.
      • Mattes M.D.
      • Mailhot Vega R.B.
      • Escorcia F.E.
      • Lawton C.
      • Greenberger J.
      • et al.
      Pathways for recruiting and retaining women and underrepresented minority clinicians and physician scientists into the radiation oncology workforce: a summary of the 2019 ASTRO/NCI Diversity Symposium session at the ASTRO Annual Meeting.
      ,

      American Society of Radiation Oncology. Diversity, equity, and inclusion in radiation oncology. https://www.astro.org/Meetings-and-Education/DEI-in-Education/DEI-in-RO May 29, 2022.

      ].
      The current analysis also implies that the “staying power” of a hashtag can be related to both the hashtag structure itself and its related topic. For example, #RadOnc is a practical hashtag relating to a worldwide common topic. It has been initiated since more than eight years and its use will likely continue to expand in the foreseeable future. While #RTsim is also a practical hashtag, its use along the tracking period was only limited to five occurrences, and this is likely related to the unpopularity of the topic in the Twitter community. From the other hand, #WomenWhoCurie is considered a long hashtag with 13 characters. Its promotion by influential organizations along its relation to a current topic of interest yielded an increase in its use in the post-deployment tracking periods. A third closely related factor to structure and topic is the hashtag longevity. Longevity is defined as the amount of time during which it remains significantly active [
      • Bruns A.
      • Stieglitz S.
      Quantitative approaches to comparing communication patterns on Twitter.
      ]. #RadOnc is a long-standing hashtag with committed long-term contributor with an established “staying power”, but future tracking is needed to evaluate the “staying power” and longevity of #WomenWhoCurie and #DEIinRO. The continued growth in the number of users for #RadOnc and #MedPhys throughout post-deployment area despite that a peak had been reached before, reflects well the longevity of these hashtags.
      From another perspective, determining the ideal number of hashtags is also an iterative process [
      • Kutikov A.
      • Woo H.H.
      • Catto J.W.
      Urology tag ontology project: standardizing social media communication descriptors.
      ], especially that most of the hashtags use occurs in an ad hoc basis [
      • Katz M.S.
      • Utengen A.
      • Anderson P.F.
      • Thompson M.A.
      • Attai D.J.
      • Johnston C.
      • et al.
      Disease-specific hashtags for online communication about cancer care.
      ]. Similarly to our urology colleagues [
      • Kutikov A.
      • Woo H.H.
      • Catto J.W.
      Urology tag ontology project: standardizing social media communication descriptors.
      ], we attempted the creation of a balanced list that would cover all the aspects of care, while preventing the formation of an exhaustive list that would submit communication to a low-level classification task. Regardless, six hashtags were removed from the list and future assessment might result in further trimming of the list.
      Most of the Twitter-related, health-focused analysis has been descriptive so far, focusing on pattern of use and trends of information exchange. With the current advancement of machine learning, future effort will likely remodel the communication character in the social platforms, to a diagnostic, predictive, and possibly a therapeutic aspect [
      • Sulthana A.R.
      • Jaithunbi A.
      • Ramesh L.S.
      Sentiment analysis in twitter data using data analytic techniques for predictive modelling.
      ]. With this potential, the radiation oncology community can take precedence in leading the way to incorporate every possible effort towards a personalized and improved patient care.
      Despite the gained popularity of our list, it still has some limitations. First, the list is currently restricted to the English language which limits its use among non-English speaking community. Second, while our analysis included the number of tweets and the stakeholders, it could not be extended to content analysis. Finally, the list dissemination strategy has been so far limited to ASTRO meeting presentations. To further increase the list use awareness, other directed dissemination strategies to radiation oncology residency programs and private practices should be undertaken, both on a national and internal levels.

      5. Conclusion

      To enhance the radiation oncology online communication, we established a set of 33 hashtags and tracked their use for two years. These hashtags are used by physicians, patients, and media to aid in communication about radiation oncology. Given the continuous universal interaction online, the scheme of structuring hashtags sets is expected to need regular updates. Future enhancement of online communication might require the inclusion of non-English hashtags and diversification of dissemination strategies.

      Declaration of Competing Interest

      The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.

      Appendix A. Supplementary data

      The following are the Supplementary data to this article:

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