These are the slides for my talk presented at the STI 2016 in Valencia. The paper dx.doi.org/10.1016/j.joi.2016.04.015 contains additional information regarding this presentation.

1. Normalization of Mendeley
reader impact on the reader- and
paper-side
Robin Haunschild Lutz Bornmann
09/16/2016

2. Introduction
Altmetrics
Alternative metrics, closely related to article level metrics
Facebook: posts, likes, ...
Twitter: tweets, retweets, ...
Mendeley, CiteULike, Zotero, ...: readers (reader counts,
bookmarks, saves, ...)
News outlets: stories, mentions
Blogs: stories, mentions
...
Two major fields of altmetrics research
1. Meaning of altmetrics counts
2. Normalization of altmetrics counts
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3. Introduction
Mendeley
Online reference manager
Desktop and mobile applications
Social, academic networking component
API for user statistics
Global web traffic rank from Alexa
Mendeley reader impact Robin Haunschild et al. 3

4. Introduction
Research Questions
1. Is normalization important for Mendeley reader counts?
2. Which normalization procedures are possible?
3. Can analogous versions to citing-side and cited-side
normalizations be done using Mendeley reader counts?
4. How do the methods differ?
Mendeley reader impact Robin Haunschild et al. 4

5. Data set
Data set
DOIs from WoS papers from 2012 (Na = 1, 133, 224 articles
and Nr = 64, 960 reviews)
Search via Mendeley API for DOI in December 2014
Overall 94.8% of the articles and 96.6% of the reviews were
found on Mendeley
9,352,424 Mendeley reader counts for the articles and
1,335,764 for the reviews.
0.05% of the article readers and 0.04% of the review
readers did not share their (sub-)disciplinary information
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6. Example data from Mendeley
Data available from Mendeley
Input DOI, PubMedID, ... (e.g., 10.1063/1.4769790, Insensitivity
of the error of the minimally empirical hybrid functional
revTPSSh to its parameters):
Total reader count (here: 9)
Reader count per academic status (here: 2 Researchers, 1
Other, 3 Professors, 2 PhD Students, and 1 Associate
Professor)
Reader count per Mendeley discipline (here: 1 in
Materials Science, 1 in Physics, 5 in Chemistry, 1 in Social
Sciences, and 1 in Economics)
Reader count per country (here: 1 in USA, 1 in the Vatican,
and 1 in South Korea)
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7. Mendeley readers per document type
Mendeley readers per article in the Mendeley disciplines
Mendeley reader impact Robin Haunschild et al. 7

8. Mendeley readers per document type (cont’d)
Mendeley readers per review in the Mendeley disciplines
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9. Mendeley readers per document type (cont’d)
Mendeley readers per article in the top WoS subject
categories
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10. Mendeley readers per document type (cont’d)
Mendeley readers per review in the top WoS subject
categories
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11. Cited-side and citing-side methods
Cited-side
1. Counting all citations a paper has received
2. Normalization of citation counts with respect to the
scientific field of the cited paper
Analogous version for Mendeley reader counts: paper-side
Citing-side
1. Counting all citations a paper has received separately for
each scientific field of the citing paper
2. Normalization of citation counts with respect to the scientific
field of the citing paper
Analogous version for Mendeley reader counts: reader-side
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12. Method
Paper-side Normalization
Average number of readers per paper (ρ) in a scientific field
(here: WoS subject category), document type, and publication
year:
ρc =
1
Nc
Nc
i=1
Ri (1)
Nc: Number of papers in a WoS subject category, document type,
and publication year
Ri : Number of reader counts of paper i
NRSi =
Ri
ρc
(2)
NRSi : Normalized Reader Score for paper i
Multiplicative (or fractional or full counting) for papers with WoS
subject categories
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13. Method
Paper-side Normalization (cont’d)
Average over a set of papers of a specific unit:
MNRS =
1
N
N
i=1
NRSi (3)
N: Number of papers in a specific research unit
Interpretation
Analogous to MNCS:
(M)NRS ≈ 1: average reader impact of paper
(M)NRS < 1: below average reader impact of paper
(M)NRS > 1: above average reader impact of paper
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14. Method
Reader-side Normalization
Average number of readers per paper (ρ) in a scientific field
(here: Mendeley discipline), document type, and publication
year:
ρd =
1
Nd
Nd
i=1
Rid (4)
Nd : Number of papers in a Mendeley discipline, document type, and
publication year
Rid : Number of reader counts of paper i in Mendeley discipline d
βid =
Rid
ρd
(5)
βid : Normalized Reader Score for paper i in Mendeley discipline d
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15. Method
Reader-side Normalization (cont’d)
Sum over all Mendeley disciplines yields a paper-based reader
impact value:
DNRSi =
D
d=1
βid (6)
D: Number of Mendeley disciplines where paper i has readers.
DNRSi : Discipline Normalized Reader Score of paper i
Average over a set of papers of a specific unit:
MDNRS =
1
N
N
i=1
DNRSi (7)
N: Number of papers in a specific research unit
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16. Spearman correlation coefficients for journals
MDNRS vs. MNRS for different OECD categories
OECD category rs No. of journals
Natural sciences 0.75 3337
Engineering and technology 0.81 1556
Medical and health sciences 0.82 2855
Agricultural sciences 0.89 385
Social sciences 0.83 1920
Humanities 0.42 563
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17. Additional Information
More details
DOI: 10.1016/j.joi.2016.04.015
Submission history
22 February, 2016: Upload of Manuscript (version 1) to
Figshare and submission of revised version to JoI.
07 March, 2016: Submission of abstract for this contribution
14 March/29 March, 2016: Submission deadline for STI
contributions
22 April, 2016: Manuscript accepted by JoI and upload of
final manuscript version to Figshare.
30 May, 2016: Formal acceptance of this contribution to this
conference.
DOI: 10.1016/j.joi.2016.04.015, published in the August
2016 issue of JoI.
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18. Summary and Conclusions
Answering the Research Questions
Yes, normalization is important for Mendeley reader counts.
Raw reader counts should not be used for impact
assessment.
Paper-side and reader-side normalizations are possible.
The paper-side normalization is the analogue of the
cited-side normalization, and the reader-side normalization
is the analogue of the citing-side normalization.
The reader-side and paper-side normalization methods
provide slightly different rankings, e.g. for journals.
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19. Summary and Conclusions
Normalization of Mendeley reader counts
Two different methods for normalization of Mendeley reader
counts were presented.
Both methods correlate larger than expected for most
journals.
Outlook
Normalization with respect to Mendeley disciplines has
been done.
Is it useful to normalize with respect to:
academic status groups or
country affiliations
of Mendeley readers?
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