However, citations as a metric have various disadvantages, including the fact that they take a very long time to accumulate. Citations are the basis for metrics like the h-index and its derivatives, which are used to evaluate the productivity and impact of individual researchers, or the impact factor, which is used to evaluate the scientific impact of journals. Citations in peer-reviewed articles referencing other articles are a widely accepted measure of scientific impact. Scientists, research organizations, and funding agencies require metrics to measure the impact of research. 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. Social impact measures based on tweets are proposed to complement traditional citation metrics. 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. Top-cited articles can be predicted from top-tweeted articles with 93% specificity and 75% sensitivity.Ĭonclusions: Tweets can predict highly cited articles within the first 3 days of article publication. 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). 001) could explain 27% of the variation of citations. A linear multivariate model with time and tweets as significant predictors (P <. 72 for the log-transformed Google Scholar citations, but were less clear for Scopus citations and rank correlations. The Pearson correlations between tweetations and citations were moderate and statistically significant, with correlation coefficients ranging from. 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. Results: A total of 4208 tweets cited 286 distinct JMIR articles. A heuristic to predict the top-cited articles in each issue through tweet metrics was validated. 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. Methods: Between July 2008 and November 2011, all tweets containing links to articles in the Journal of Medical Internet Research (JMIR) were mined. 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. However, the relationship of the these new metrics to traditional metrics such as citations is not known. 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. See correction statement in: īackground: Citations in peer-reviewed articles and the impact factor are generally accepted measures of scientific impact. Related ArticleThis is a corrected version. JMIR Bioinformatics and Biotechnology 23 articles.JMIR Biomedical Engineering 61 articles.JMIR Perioperative Medicine 69 articles.Journal of Participatory Medicine 71 articles.JMIR Rehabilitation and Assistive Technologies 177 articles.JMIR Pediatrics and Parenting 230 articles.Interactive Journal of Medical Research 259 articles.JMIR Public Health and Surveillance 964 articles.Journal of Medical Internet Research 6898 articles.
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