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Field-weighting readership: how does it compare to field-weighting citations?

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Field-weighting readership: how does it compare to field-weighting citations?

Authors: Sarah Huggett, Eleonora Palmaro, Christopher James

Workshop Website: http://www.altmetrics.ntuchess.com/AROSIM2018/

Published in: Technology
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Field-weighting readership: how does it compare to field-weighting citations?

  1. 1. | 0 Sarah Huggett, Chris James, Eleonora Palmaro AROSIM 2018 Altmetrics for Research Outputs Measurement and Scholarly Information Management Field-Weighting Readership: How Does it Compare to Field- Weighting Citations?
  2. 2. | 1 Elsevier and information analytics
  3. 3. | 2 Key Findings • There is a strong correlation between publications read (Mendeley reads) and publications cited (Scopus citations). To some extent this is a function of size. Mendeley readers geographic distribution may also play a role. • There is a strong correlation between FWRI and FWCI, thereby removing any size effect, as well as any specialisation effect. • For most fields except the Humanities there appears to be a small FWRI advantage, particularly pronounced in the Agricultural and Social Sciences. Variations per country overall tend to hold true per field.
  4. 4. | 3 Size matters: correlation between reads and cites
  5. 5. | 4 Effect of Mendeley readers geographic distribution?
  6. 6. | 5 FWCI and FWRI: normalising for size, age, type, field
  7. 7. | 6 Size is not all: correlation between FWCI and FWRI
  8. 8. | 7 Variations per country tend to hold true per OECD field
  9. 9. | 8 The FWRI advantage
  10. 10. | 9 Conclusions • There is a strong correlation between number of papers cited and read per country, which doesn’t appear to be solely a function of size. • The correlation between FWRI and FWCI is lower but still strong. Variations per country tend to hold true per field. • Specific regional patterns may be influenced by the geographic distribution of Mendeley readers. • FWRI appears as a robust metrics that can offer a useful complement to FWCI, in that it provides insights on a different part of the scholarly communications cycle. • More detailed analyses are welcome to further test the metrics at different aggregation levels. It would also be interesting to see how it compares to other indicator types (e.g. downloads, views, altmetrics).
  11. 11. | 10 www.elsevier.com/research-intelligence Thank you Any questions? s.huggett@elsevier.com

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