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      Social media for research, education and practice in rheumatology

      , ,
      Rheumatology International
      Springer Science and Business Media LLC

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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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            Social Medicine: Twitter in Healthcare

            Social media enables the public sharing of information. With the recent emphasis on transparency and the open sharing of information between doctors and patients, the intersection of social media and healthcare is of particular interest. Twitter is currently the most popular form of social media used for healthcare communication; here, we examine the use of Twitter in medicine and specifically explore in what capacity using Twitter to share information on treatments and research has the potential to improve care. The sharing of information on Twitter can create a communicative and collaborative atmosphere for patients, physicians, and researchers and even improve quality of care. However, risks involved with using Twitter for healthcare discourse include high rates of misinformation, difficulties in verifying the credibility of sources, overwhelmingly high volumes of information available on Twitter, concerns about professionalism, and the opportunity cost of using physician time. Ultimately, the use of Twitter in healthcare can allow patients, healthcare professionals, and researchers to be more informed, but specific guidelines for appropriate use are necessary.
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              Twelve tips for using Twitter as a learning tool in medical education.

              Twitter is an online social networking service, accessible from any Internet-capable device. While other social networking sites are online confessionals or portfolios of personal current events, Twitter is designed and used as a vehicle to converse and share ideas. For this reason, we believe that Twitter may be the most likely candidate for integrating social networking with medical education. Using current research in medical education, motivation and the use of social media in higher education, we aim to show the ways Twitter may be used as a learning tool in medical education. A literature search of several databases, online sources and blogs was carried out examining the use of Twitter in higher education. We created 12 tips for using Twitter as a learning tool and organized them into: the mechanics of using Twitter, suggestions and evidence for incorporating Twitter into many medical education contexts, and promoting research into the use of Twitter in medical education. Twitter is a relatively new social medium, and its use in higher education is in its infancy. With further research and thoughtful application of media literacy, Twitter is likely to become a useful adjunct for more personalized teaching and learning in medical education.
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                Author and article information

                Journal
                Rheumatology International
                Rheumatol Int
                Springer Science and Business Media LLC
                0172-8172
                1437-160X
                February 2020
                December 20 2019
                February 2020
                : 40
                : 2
                : 183-190
                Article
                10.1007/s00296-019-04493-4
                31863133
                9b870c31-636f-466f-9950-f8e2e68c32e8
                © 2020

                http://www.springer.com/tdm

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