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      Who should you be following? The top 100 social media influencers in orthopaedic surgery

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          Abstract

          BACKGROUND

          Social media has been credited with the potential to transform medicine, and Twitter was recently named “an essential tool” for the academic surgeon. Despite this, peer-to-peer and educational influence on social media has not been studied within orthopaedic surgery. This knowledge is important to identify who is controlling the conversation about orthopaedics to the public. We hypothesized that the plurality of top influencers would be sports medicine surgeons, that social media influence would not be disconnected from academic productivity, and that some of the top social media influencers in orthopaedic surgery would not be orthopaedic surgeons.

          AIM

          To identify the top 100 social media influencers within orthopaedics, characterize who they are, and relate their social media influence to academic influence.

          METHODS

          Twitter influence scores for the topic “orthopaedics” were collected in July 2018 using Right Relevance software. The accounts with the top influence scores were linked to individual names, and the account owners were characterized with respect to specialty, subspecialty, practice setting, location, board certification, and academic Hirsch index ( h-index).

          RESULTS

          Seventy-eight percent of top influencers were orthopaedic surgeons. The most common locations included California (13%), Florida (8%), New York (7%), United Kingdom (7%), Colorado (6%), and Minnesota (6%). The mean academic h-index of the top influencers ( n = 79) was 13.67 ± 4.12 (mean ± 95%CI) and median 7 (range 1-89) (median reported h-index of academic orthopaedic faculty is 5 and orthopaedic chairpersons is 13). Of the 78 orthopaedic surgeons, the most common subspecialties were sports medicine (54%), hand and upper extremity (18%), and spine (8%). Most influencers worked in private practice (53%), followed by academics (17%), privademics (14%), and hospital-based (9%). All eligible orthopaedic surgeons with publicly-verifiable board certification statuses were board-certified ( n = 74).

          CONCLUSION

          The top orthopaedic social media influencers on Twitter were predominantly board-certified, sports-medicine subspecialists working in private practice in the United States. Social media influence was highly concordant with academic productivity as measured by the academic h-index. Though the majority of influencers are orthopaedic surgeons, 22% of top influencers on Twitter are not, which is important to identify given the potential for these individuals to influence patients’ perceptions and expectations. This study also provides the top influencer network for other orthopaedic surgeons to engage with on social media to improve their own social media influence.

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          Most cited references 29

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          Can Tweets Predict Citations? Metrics of Social Impact Based on Twitter and Correlation with Traditional Metrics of Scientific Impact

          Background Citations in peer-reviewed articles and the impact factor are generally accepted measures of scientific impact. Web 2.0 tools such as Twitter, blogs or social bookmarking tools provide the possibility to construct innovative article-level or journal-level metrics to gauge impact and influence. However, the relationship of the these new metrics to traditional metrics such as citations is not known. Objective (1) To explore the feasibility of measuring social impact of and public attention to scholarly articles by analyzing buzz in social media, (2) to explore the dynamics, content, and timing of tweets relative to the publication of a scholarly article, and (3) to explore whether these metrics are sensitive and specific enough to predict highly cited articles. Methods Between July 2008 and November 2011, all tweets containing links to articles in the Journal of Medical Internet Research (JMIR) were mined. For a subset of 1573 tweets about 55 articles published between issues 3/2009 and 2/2010, different metrics of social media impact were calculated and compared against subsequent citation data from Scopus and Google Scholar 17 to 29 months later. A heuristic to predict the top-cited articles in each issue through tweet metrics was validated. Results A total of 4208 tweets cited 286 distinct JMIR articles. The distribution of tweets over the first 30 days after article publication followed a power law (Zipf, Bradford, or Pareto distribution), with most tweets sent on the day when an article was published (1458/3318, 43.94% of all tweets in a 60-day period) or on the following day (528/3318, 15.9%), followed by a rapid decay. The Pearson correlations between tweetations and citations were moderate and statistically significant, with correlation coefficients ranging from .42 to .72 for the log-transformed Google Scholar citations, but were less clear for Scopus citations and rank correlations. A linear multivariate model with time and tweets as significant predictors (P < .001) could explain 27% of the variation of citations. Highly tweeted articles were 11 times more likely to be highly cited than less-tweeted articles (9/12 or 75% of highly tweeted article were highly cited, while only 3/43 or 7% of less-tweeted articles were highly cited; rate ratio 0.75/0.07 = 10.75, 95% confidence interval, 3.4–33.6). Top-cited articles can be predicted from top-tweeted articles with 93% specificity and 75% sensitivity. Conclusions Tweets can predict highly cited articles within the first 3 days of article publication. Social media activity either increases citations or reflects the underlying qualities of the article that also predict citations, but the true use of these metrics is to measure the distinct concept of social impact. Social impact measures based on tweets are proposed to complement traditional citation metrics. The proposed twimpact factor may be a useful and timely metric to measure uptake of research findings and to filter research findings resonating with the public in real time.
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            'What's happening?' A content analysis of concussion-related traffic on Twitter.

            Twitter is a rapidly growing social networking site (SNS) with approximately 124 million users worldwide. Twitter allows users to post brief messages ('tweets') online, on a range of everyday topics including those dealing with health and wellbeing. Currently, little is known about how tweets are used to convey information relating to specific injuries, such as concussion, that commonly occur in youth sports. The purpose of this study was to analyse the online content of concussion-related tweets on the SNS Twitter, to determine the concept and context of mild traumatic brain injury as it relates to an online population. A prospective observational study using content analysis. Twitter traffic was investigated over a 7-day period in July 2010, using eight concussion-related search terms. From the 3488 tweets identified, 1000 were randomly selected and independently analysed using a customised coding scheme to determine major content themes. The most frequent theme was 'news' (33%) followed by 'sharing personal information/situation' (27%) and 'inferred management' (13%). Demographic data were available for 60% of the sample, with the majority of tweets (82%) originating from the USA, followed by Asia (5%) and the UK (4.5%). This study highlights the capacity of Twitter to serve as a powerful broadcast medium for sports concussion information and education.
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              #colorectalsurgery: #colorectalsurgery

              The use of social media platforms among healthcare professionals is increasing. A Twitter social media campaign promoting the hashtag #colorectalsurgery was launched with the aim of providing a specialty-specific forum to collate discussions and science relevant to an engaged, global community of coloproctologists. This article reviews initial experiences of the early adoption, engagement and utilization of this pilot initiative.
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                Author and article information

                Contributors
                Journal
                World J Orthop
                WJO
                World Journal of Orthopedics
                Baishideng Publishing Group Inc
                2218-5836
                18 September 2019
                18 September 2019
                : 10
                : 9
                : 327-338
                Affiliations
                Department of Orthopaedic Surgery, Massachusetts General Hospital/Harvard Medical School, Boston, MA 02114, United States. igans1@ 123456jhmi.edu
                Department of Plastic and Reconstructive Surgery, Johns Hopkins University School of Medicine, Baltimore, MD 21205, United States
                Department of Orthopaedic Surgery, Massachusetts General Hospital/Harvard Medical School, Boston, MA 02114, United States
                Department of Orthopaedic Surgery, Johns Hopkins University School of Medicine, Baltimore, MD 21205, United States
                Author notes

                Author contributions: Varady NH, Chandawarkar AA, Gans I conceived the research; Kernkamp WA and Varady NH collected the data; Varady NH analyzed the data; Varady NH wrote the paper; Varady NH, Chandawarkar AA, Kernkamp WA, Gans I critically revised the paper.

                Corresponding author: Itai Gans, MD, Surgeon, Department of Orthopaedic Surgery, Johns Hopkins University School of Medicine, 601 North Caroline Street, JHOC 5th Floor, Baltimore, MD 21205, United States. igans1@ 123456jhmi.edu

                Telephone: ‭+1-973-7236174‬‬‬‬‬‬‬‬‬

                Article
                jWJO.v10.i9.pg327
                10.5312/wjo.v10.i9.327
                6766466
                ©The Author(s) 2019. Published by Baishideng Publishing Group Inc. All rights reserved.

                This article is an open-access article which was selected by an in-house editor and fully peer-reviewed by external reviewers. It is distributed in accordance with the Creative Commons Attribution Non Commercial (CC BY-NC 4.0) license, which permits others to distribute, remix, adapt, build upon this work non-commercially, and license their derivative works on different terms, provided the original work is properly cited and the use is non-commercial.

                Categories
                Scientometrics

                orthopedics, influence, impact, twitter, orthopaedics, social media

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