This document provides an overview of bibliometric visualizations using VOSviewer software. It discusses the explosive growth of scientific literature and available bibliographic data sources. VOSviewer allows visualization of co-authorship, citation-based, and term co-occurrence networks. Hands-on demonstrations are provided for creating co-authorship maps, citation maps of publications and journals, and term maps. Bibliometric maps provide insights into the structure and relationships within a research field.
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Bibliometrische visualisaties voor het bijhouden van wetenschappelijke literatuur
1. Bibliometrische visualisaties voor het bijhouden van
wetenschappelijke literatuur
Nees Jan van Eck
Centre for Science and Technology Studies (CWTS), Leiden University
VOGIN-IP-lezing
21 oktober 2021
2. About myself
• Master in computer science
• PhD thesis on bibliometric mapping of science
• Senior researcher at CWTS
– Bibliometric network analysis and visualization
– Bibliometric data sources
– Bibliometric indicators
• Head of ICT
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3. Centre for Science and Technology Studies (CWTS)
• Research center at Leiden University
• Science and technology studies, with a considerable
emphasis on scientometrics
• About 50 staff members
• Our mission: Making the science system better!
• Full access to large bibliographic database (Web of
Science, Scopus, Dimensions, PubMed, PATSTAT,
etc.)
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4. Centre for Science and Technology Studies (CWTS)
• Basic research:
– Quantitative science studies
– Science and evaluation studies
– Science, technology and innovation studies
• Commissioned research:
– Bibliometric studies for universities, funding organizations, governments, scientific publishers, etc.
– Mostly done using the in-house databases of CWTS
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5. Program
• Introduction
• Hands-on assignments
– Data collection
– VOSviewer:
• Co-authorship maps
• Citation-based maps
• Term maps
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7. Explosive growth of scientific literature
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“A new scientific paper is published
every 30 seconds and there are
10,000 updates to PubMed every day”
“It is impossible for humans alone to
process all of the complex information
potentially available to them for the
advancement of scientific research”
James Chandler, November 2016, BenevolentAI
9. Bibliographic data sources
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Web of Science Scopus Dimensions
Journals 20,000 25,000 50,000
Publications 60 million 50 million 110 million
Citations 1.4 billion 1.5 billion 1.2 billion
10. Bibliometric networks
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WoS
Scopus
Dimensions
Lens
MAG
Semantic Scholar
PubMed
Europe PMC
Crossref
Citation network
of pubs / journals / authors / orgs / countries
Co-authorship network
of authors / orgs / countries
Co-citation network
of pubs / journals / authors / orgs / countries
Co-occurrence network
of keywords / terms
Bibliographic coupling network
of pubs / journals / authors
Bibliographic
data source
12. VOSviewer
• Focus on visualization of scientometric networks
• Support for large number of data sources
• Text mining functionality
• Advanced visualization features
• Relatively easy to use
• Limited analysis options
• Developed at CWTS
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13. Users of VOSviewer
• Researchers
• Research institutions
• Research funders
• Scientific publishers
• Industry
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26. Downloading Web of Science data
Pay attention to the following:
• Use the Web of Science Core Collection database
• Use the Full Record and Cited References option
• Use a suitable file format:
– VOSviewer supports both the plain text and the tab-delimited format
– Tab-delimited files can be easily processed using spreadsheet software
• We use the tab-delimited format
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49. Determining relatedness based on citation data
• Determining relatedness of publications, journals, authors, etc. based on
citation data:
– Direct citation relations
– Bibliographic coupling relations
– Co-citation relations
• VOSviewer supports all three types of citation-based relations
• Another tool, CitNetExplorer, is focused entirely on direct citation relations
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50. Direct citation relations
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P1 P2
P1 and P2 are related because P1 has cited P2
(i.e., P2 appears in the reference list of P1)
56. Comparison of different types of citation-based
relations
• Direct citation relations:
– Focus on recent publications
– Stable (direct citation relations won’t change in the future)
– Some publications may have no direct citation relations
• Bibliographic coupling relations:
– Focus on recent publications
– Stable (bib. coupling relations won’t change in the future)
– Publications almost always have bib. coupling relations
• Co-citation relations:
– Focus on older publications
– Unstable (co-citation relations may change in the future)
– Some publications may have no co-citation relations
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59. Interpretation of a citation-based map
• Size:
– The larger an item (e.g., author or journal), the larger the number of publications of the item
• Distance:
– In general, the smaller the distance between two items, the higher the relatedness of the items, as
measured by citations, bibliographic coupling or co-citations
– The horizontal and vertical axes have no special meaning; maps can be freely rotated and flipped
• Colors:
– Colors indicate clusters of strongly related items
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60. Citation-based maps supported by VOSviewer
• Citation and bibliographic coupling maps:
– Publications
– Journals
– Authors
– Organizations
– Countries
• Co-citation maps:
– Cited references
– Cited journals
– Cited authors (first author only in the case of Web of Science)
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64. Interpretation of a term map
• Size:
– The larger a term, the higher the frequency of occurrence of the term
• Distance:
– In general, the smaller the distance between two terms, the higher the relatedness of the terms, as
measured by co-occurrences
– The horizontal and vertical axes have no special meaning; maps can be freely rotated and flipped
• Colors:
– Colors indicate clusters of closely related terms
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75. Aim of bibliometric maps
• To provide an overview of the structure of the scientific literature in a certain
domain or on a certain topic
• Applications:
– To identify the main research areas within a scientific field
– To get insight into the size of the different areas
– To see how the areas relate to each other
• Bibliometric maps are especially useful when one has to deal with a relatively
large body of literature
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77. Use of scientometric visualizations
• Visualizations can be used to make complex information more accessible
• Visualizations need to be used in combination with expert knowledge:
– Confirm expert knowledge
– Challenge expert knowledge
– Draw expert’s attention to interesting information
• Be aware of information loss and methodological sensitivity
• Visualizations can also be used pragmatically to attract attention and to ‘sell
a message’
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79. Course: Visualizing Science Using VOSviewer
• January 25-28, 2022
• 4 half-day online sessions
• Participants are introduced into the main techniques for visualizing science
• Special attention is paid to applications in a research evaluation and
research management context
• The course has an interactive format and the small group size allows
participants to practice extensively with the VOSviewer software
• www.cwts.nl
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