Search (4 results, page 1 of 1)

  • × author_ss:"Haunschild, R."
  • × author_ss:"Bornmann, L."
  1. Bornmann, L.; Haunschild, R.: Relative Citation Ratio (RCR) : an empirical attempt to study a new field-normalized bibliometric indicator (2017) 0.00 
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    Abstract
    Hutchins, Yuan, Anderson, and Santangelo (2015) proposed the Relative Citation Ratio (RCR) as a new field-normalized impact indicator. This study investigates the RCR by correlating it on the level of single publications with established field-normalized indicators and assessments of the publications by peers. We find that the RCR correlates highly with established field-normalized indicators, but the correlation between RCR and peer assessments is only low to medium.
    Type
    a
  2. Bornmann, L.; Bauer, J.; Haunschild, R.: Distribution of women and men among highly cited scientists (2015) 0.00 
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    Type
    a
  3. Bornmann, L.; Haunschild, R.: Overlay maps based on Mendeley data : the use of altmetrics for readership networks (2016) 0.00 
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    Abstract
    Visualization of scientific results using networks has become popular in scientometric research. We provide base maps for Mendeley reader count data using the publication year 2012 from the Web of Science data. Example networks are shown and explained. The reader can use our base maps to visualize other results with the VOSViewer. The proposed overlay maps are able to show the impact of publications in terms of readership data. The advantage of using our base maps is that it is not necessary for the user to produce a network based on all data (e.g., from 1 year), but can collect the Mendeley data for a single institution (or journals, topics) and can match them with our already produced information. Generation of such large-scale networks is still a demanding task despite the available computer power and digital data availability. Therefore, it is very useful to have base maps and create the network with the overlay technique.
    Type
    a
  4. Bornmann, L.; Haunschild, R.: ¬An empirical look at the nature index (2017) 0.00 
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    Abstract
    In November 2014, the Nature Index (NI) was introduced (see http://www.natureindex.com) by the Nature Publishing Group (NPG). The NI comprises the primary research articles published in the past 12 months in a selection of reputable journals. Starting from two short comments on the NI (Haunschild & Bornmann, 2015a, 2015b), we undertake an empirical analysis of the NI using comprehensive country data. We investigate whether the huge efforts of computing the NI are justified and whether the size-dependent NI indicators should be complemented by size-independent variants. The analysis uses data from the Max Planck Digital Library in-house database (which is based on Web of Science data) and from the NPG. In the first step of the analysis, we correlate the NI with other metrics that are simpler to generate than the NI. The resulting large correlation coefficients point out that the NI produces similar results as simpler solutions. In the second step of the analysis, relative and size-independent variants of the NI are generated that should be additionally presented by the NPG. The size-dependent NI indicators favor large countries (or institutions) and the top-performing small countries (or institutions) do not come into the picture.
    Type
    a

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