Search (2 results, page 1 of 1)

  • × author_ss:"Eysenbach, G."
  • × theme_ss:"Informetrie"
  1. Kudlow, P.; Dziadyk, D.B.; Rutledge, A.; Shachak, A.; Eysenbach, G.: ¬The citation advantage of promoted articles in a cross-publisher distribution platform : a 12-month randomized controlled trial (2020) 0.00 
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    Abstract
    There is currently a paucity of evidence-based strategies that have been shown to increase citations of peer-reviewed articles following their publication. We conducted a 12-month randomized controlled trial to examine whether the promotion of article links in an online cross-publisher distribution platform (TrendMD) affects citations. In all, 3,200 articles published in 64 peer-reviewed journals across eight subject areas were block randomized at the subject level to either the TrendMD group (n = 1,600) or the control group (n = 1,600) of the study. Our primary outcome compares the mean citations of articles randomized to TrendMD versus control after 12 months. Articles randomized to TrendMD showed a 50% increase in mean citations relative to control at 12 months. The difference in mean citations at 12 months for articles randomized to TrendMD versus control was 5.06, 95% confidence interval [2.87, 7.25], was statistically significant (p?<?.001) and found in three of eight subject areas. At 6 months following publication, articles randomized to TrendMD showed a smaller, yet statistically significant (p = .005), 21% increase in mean citations, relative to control. To our knowledge, this is the first randomized controlled trial to demonstrate how an intervention can be used to increase citations of peer-reviewed articles after they have been published.
    Type
    a
  2. Callahan, A.; Hockema, S.; Eysenbach, G.: Contextual cocitation : augmenting cocitation analysis and its applications (2010) 0.00 
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    Abstract
    In this work, a novel method of cocitation analysis, coined contextual cocitation analysis, is introduced and described in comparison to traditional methods of cocitation analysis. Equations for quantifying contextual cocitation strength are introduced and their implications explored using theoretical examples alongside the application of contextual cocitation to a series of BioMed Central publications and their cited resources. Based on this work, the implications of contextual cocitation for understanding the granularity of the relationships created between cited published research and methods for its analysis are discussed. Future applications and improvements of this work, including its extended application to the published research of multiple disciplines, are then presented with rationales for their inclusion.
    Type
    a

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