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The Google Scholar Revolution:
a big data bibliometric tool
Google Scholar Day: Changing current evaluation paradigms
Cybermetrics Lab (IPP–CSIC) Madrid, 20 February 2017
Enrique Orduña-Malea, Alberto Martín-Martín, Juan M. Ayllón,
Emilio Delgado López-Cózar
EC3 Research Group-Scholar Division
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EC3 Research Group – Google Scholar Division
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se
arc
h e
ng
ine
Bib
lio
gra
ph
ic s
ea
rch
to
ol
Bib
liom
etric
too
l The two faces of Google Scholar
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The google search familly. Its goal: finding information
Scholar Search
Scholar Citations
Scholar Metrics
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Simple
Easy
Fast
Easy to understand and use
Universal, international, global
Multilingual
Free
Why is it successful?
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2012 2011
2004
Google’s incursion in Bibliometrics
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Studying it from the bibliometric perspective:
EC3-Scholar Division
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Opening the academic Pandora’s Box 2008-
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Journals Authors Publishers
Multifaceted model
Library & Information Sciences (Spain)
http://www.biblioteconomia-documentacion-española.infoec3.es
Bibliometrics & Scientometrics (International)
http://www.scholar-mirrors.infoec3.es
What have we analyzed? Intensive, extensive, and obsessive work
Conferences
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• Publication data about 49,930 A&H and SS professors working in public
Spanish universities was extracted from Google Scholar in 2012
• Only authors in the first tercile are displayed
• 68 discipline rankings (49 in Social Sciences and Law, 39 in Arts and
Humanities)
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Indicators
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Collecting data Max. number of hits per page
February 2013: from 100 to 20
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Sample of highly cited books (top 3%)
published by ~49k A&H and SS
professors working
in public Spanish universities
Data collected from Google Scholar in
2012 (n ~ 7203)
68 discipline rankings
(49 in Social Sciences and Law,
39 in Arts and Humanities)
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Indicators: Nº of books, and sum
of citations (relative to highest
element in the ranking)
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Indicators
H5 Index
H5 Median
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Spanish Journals ± 2.500
SJR-Scopus
506
JCR
114 Google Scholar Metrics
1299
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Indicators
Extracted
directly from
Google Scholar
Metrics
Computed using the article and
citation data available in Google
Scholar Metrics
H Index of
documents
published in the
last 5 years
Median of
citation counts
for articles
published in last
5 years
Sum of
citations for
articles above
h5-index
threshold
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Classification
Core Related
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Coverage
IMPORTANT: Google Scholar Metrics
only covers journals that are indexed in
Google Scholar, have published at
least 100 articles in the last 5-year
period, and have received at least 1
citation
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PROCEEDINGS
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Citations
Multifaceted model
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LIS researchers
in Spain 336 authors in GSC
68 not in GSC
Other sources ResearcherID (WoS)
ResearchGate
Indicators Sum of citations
H Index
Nº of documents
RG Score
Impact Points
Aggregating data Highly cited docs (HCD),
% of HCD by journal, book
publisher, and institution
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The «Mirrors» approach
There are many platforms that reflect (mirror) scientific activity
on the Web. An inclusive study of the impact of scientific
activity must contemplate as many of them as possible.
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Bibliometric potential of Google Scholar
We have proved
Yes, we can
What do we know about Google Scholar?
Its strengths and weaknesses
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It’s the most used academic
search engine
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Why do we call it a big data bibliometric tool?
Source
COVERAGE
All documents
Geographic
COVERAGE
All countries
Linguistic
COVERAGE
All languages
Discipline
COVERAGE
All of them
GROWTH
Faster than WoS and
Scopus
FAST TRACK
CITATIONS
Newly published
documents indexed in
a matter of days
Big Data
Big Data
SIZE Largest bibliographic database in the world
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The search engine with the largest coverage
Size matters
Orduña-Malea, E., Ayllón, J. M., Martín-Martín, A., Delgado López-Cózar, E.. (2014). About the size of Google
Scholar: playing the numbers. arXiv preprint arXiv:1407.6239. EC3 Working Papers 18
Orduna-Malea, E., Ayllón, J. M., Martín-Martín, A., Delgado López-Cózar, E. Methods for estimating the size of Google
Scholar. Scientometrics 104 (3), 931-949
2015
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The search engine with the largest coverage
Size matters
2017
Nº documents
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2017
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Larger coverage, larger citation graph
0
0,5
1
1,5
2
2,5
3
Art & Humanities Social Sciences Sciences TOTAL
Ra
tio
of
GS
Cit
ati
on
s t
o W
oS
Cit
ati
on
s (
avg
)
Documents published in 2009 Documents published in 2014
Analysis of most documents with a DOI published in 2009 and 2014 covered by
Web of Science (~2.5 million documents)
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International
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0%
10%
20%
30%
40%
50%
60%
70%
80%
90%
100%
18
00
18
05
18
10
18
15
18
20
18
25
18
30
18
35
18
40
18
45
18
50
18
55
18
60
18
65
18
70
18
75
18
80
18
85
18
90
18
95
19
00
19
05
19
10
19
15
19
20
19
25
19
30
19
35
19
40
19
45
19
50
19
55
19
60
19
65
19
70
19
75
19
80
19
85
19
90
19
95
20
00
20
05
20
10
20
15
Proportion of documents covered by Google Scholar by language over the years
Turkish
Dutch
Chinese
Polish
Korean
Italian
Japanese
Portuguese
Spanish
French
Simplified
Chinese
German
English
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Multilingual Documents covered by Google Scholar, Web of Science & Scopus by 13 languages
(1800-2016)
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Multilingual
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Covers all
document
typologies
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Th
e a
lte
rna
tive
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Google Scholar offers a different vision of scientific production
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Web of Science documents (2009/2014) found in Google Scholar
found in GS
96%
not found in
GS
4%
96% of the searched WoS documents were found in GS. 98% if we only consider
journal articles. The rest might have been found as well if alternative search strategies
had been used.
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Martín-Martín, A., Orduña-Malea, E., Ayllón, J. M., Delgado López-Cózar, E. (2014). Does Google Scholar contain all highly cited
documents (1950-2013)?. arXiv preprint arXiv:1410.8464.
Highly cited documents in Google Scholar (1950-2013)
Half of them are not in WoS
The ones who are in WoS: very high citation correlation
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Confirmation
PRELIMINARY RESULTS:
Analysis of most documents with a DOI published in 2009 covered by Web
of Science (~1 million documents)
Citation Index N spearman.cor p.value prop.cited.gs prop.cited.wos ratio of gs_cit to wos_cit (avg)
Sciences 863801 0,94 0,00 0,97 0,95 1,68
Social Sciences 109232 0,90 0,00 0,97 0,94 2,58
Art & Humanities 13487 0,83 0,00 0,84 0,69 2,52
Sciences Social Sciences Art & Humanities
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Logical when you see their sources
elsevier.com 7.200.000
wiley.com 4,590,000
springer 3.290.000
taylor and francis 1.440.000
lww.com 1.030.000
sagepub.com 781.000
nature.com 428.000
bmj.com 370.000
Routledge 293.000
karger.com 188.000
degruyter.com 196.000
biomedcentral.com 121.000
liebertpub.com 90.900
emerald 167.000
books.google.com 14.000.000
ieee.org 2.990.000
jstor.org 2.210.000
acs.org 987.000
cambridge.org 893.000
oxfordjournals.org 872.000
acm.org 472.000
iop.org 462000
aip.org 451.000
arxiv.org 355.000
pnas.org 101.000
ams.org 98.000
sciencemag.org 62.600
nber.org 26.900
Scopus 2009
Web of Science
Google Scholar
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It has a better coverage of areas like Humanities, Social Sciences, Engineering…
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GS measures scientific impact and more
Scientific Professional
Educational Social
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What impact does it measure?
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A professional journal in Google Scholar
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We question ourselves
Drawbacks Google Scholar
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Lack of transparency
There isn’t a public master list of the sources
Google Scholar indexes (publishers,
repositories, catalogues, bibliographic
databases and repertoires, aggregators,
journals…)
There is no accurate method to estimate the
size of Google Scholar
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Similarly, even if a document has received more than 1000 citations, only the first 1000 can be displayed
when clicking the “Cited by” link
We have no control over the results we get
Are the relevant results for my needs among those 1000 results?
Usually yes… thanks to the ranking algorithm they use
Only(!) returns 1000 results for any given query
Is this really a bibliographic problem? Who is interesed in bibliographic searches of that size?
Weaknesses
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How does Google Scholar rank results?
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There is no native method to easily extract bibliographic data massively. Only one by one.
Weaknesses
There is no API. What can we use for large downloads?
A scraper
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Weaknesses
Limited filtering and sorting options (year and relevance)
≠
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Weaknesses
The advanced search form is limited to four search dimensions:
keywords, authors, source of publication (journal, conference…),
and year of publication
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No quality control of sources indexed. Peer-reviewed documents coexist with documents that haven’t gone through that process.
Is that really
a problem?
But… Google Scholar also shows which documents are covered by the Web of Science, and which of them are available from your library. YOUR CHOICE…
Weaknesses
It shows
richness rather
than a flaw
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Weaknesses
• Institutional affiliation of the authors of the documents is
available (institution, country)
• The language in which documents are written
• The typology of each document is not clear (book, journal
article, conference communication, thesis, report…). Only
books are marked as such, usually when they have been
found on Google Books
• Not all documents have an abstract
• The author-supplied keywords are not available
• The list of cited references in each article is not available
either
It doesn’t offer information regarding
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Greatest danger: manipulation
Delgado López‐Cózar, E., Robinson‐García, N., Torres‐Salinas, D. (2014). The Google
Scholar experiment: How to index false papers and manipulate bibliometric indicators.
Journal of the Association for Information Science and Technology, 65(3), 446-454.
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Errors in the data
Enough quality?
Even with «dirty» data,
it measures more and
better
Large units of analysis: no problem
Individuals: check data first
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The Googledependency
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Drawbacks:
Google Scholar Metrics
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Drawbacks:
Google Scholar Citations
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Google Scholar Citations:
Laissez faire laissez passer
Be wary of CUT / COPY – BUTTON / COMAND
bibliometric products
Don’t mix apples and oranges
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A final consideration… To what end are we measuring scientific
activity?
Spreading light where there was
darkness
Thank you very
much!